October 28, 2020
Bioconductors:
We are pleased to announce Bioconductor 3.12, consisting of 1974 software packages, 398 experiment data packages, 968 annotation packages, and 28 workflows.
There are 125 new software packages, 9 new data experiment packages, 2 new annotation packages, 1 new workflow, 2 online books, and many updates and improvements to existing packages; Bioconductor 3.12 is compatible with R 4.0.3, and is supported on Linux, 32- and 64-bit Windows, and macOS 10.14.6 Mojave or higher. This release will include an updated Bioconductor Amazon Machine Image and Docker containers.
Thank you to everyone for your contribution to Bioconductor
Visit Bioconductor BiocViews for details and downloads.
To update to or install Bioconductor 3.12:
Install R 4.0.3. Bioconductor 3.12 has been designed expressly for this version of R.
Follow the instructions at Installing Bioconductor.
There are 125 new software packages in this release of Bioconductor.
ADImpute Single-cell RNA sequencing (scRNA-seq) methods are typically unable to quantify the expression levels of all genes in a cell, creating a need for the computational prediction of missing values (‘dropout imputation’). Most existing dropout imputation methods are limited in the sense that they exclusively use the scRNA-seq dataset at hand and do not exploit external gene-gene relationship information. Here we propose two novel methods: a gene regulatory network-based approach using gene-gene relationships learnt from external data and a baseline approach corresponding to a sample-wide average. ADImpute can implement these novel methods and also combine them with existing imputation methods (currently supported: DrImpute, SAVER). ADImpute can learn the best performing method per gene and combine the results from different methods into an ensemble.
aggregateBioVar For single cell RNA-seq data collected from more than one subject (e.g. biological sample or technical replicates), this package contains tools to summarize single cell gene expression profiles at the level of subject. A SingleCellExperiment object is taken as input and converted to a list of SummarizedExperiment objects, where each list element corresponds to an assigned cell type. The SummarizedExperiment objects contain aggregate gene-by-subject count matrices and inter-subject column metadata for individual subjects that can be processed using downstream bulk RNA-seq tools.
AlpsNMR Reads Bruker NMR data directories both zipped and unzipped. It provides automated and efficient signal processing for untargeted NMR metabolomics. It is able to interpolate the samples, detect outliers, exclude regions, normalize, detect peaks, align the spectra, integrate peaks, manage metadata and visualize the spectra. After spectra proccessing, it can apply multivariate analysis on extracted data. Efficient plotting with 1-D data is also available. Basic reading of 1D ACD/Labs exported JDX samples is also available.
ANCOMBC ANCOMBC is a package for normalizing the microbial absolute abundance data due to unequal sampling fractions across samples, and identifying taxa (e.g. phyla, families, genera, species, etc.) that are differentially abundant with respect to the covariate of interest (e.g. study groups) between two or more groups of multiple samples.
AnVILBilling AnVILBilling helps monitor AnVIL-related costs in R, using queries to a BigQuery table to which costs are exported daily. Functions are defined to help categorize tasks and associated expenditures, and to visualize and explore expense profiles over time. This package will be expanded to help users estimate costs for specific task sets.
AnVILPublish Use this package to create or update AnVIL workspaces from resources such as R / Bioconductor packages. The metadata about the package (e.g., select information from the package DESCRIPTION file and from vignette YAML headings) are used to populate the ‘DASHBOARD’. Vignettes are translated to python notebooks ready for evaluation in AnVIL.
bambu bambu is a R package for multi-sample transcript discovery and quantification using long read RNA-Seq data. You can use bambu after read alignment to obtain expression estimates for known and novel transcripts and genes. The output from bambu can directly be used for visualisation and downstream analysis such as differential gene expression or transcript usage.
BayesSpace Tools for clustering and enhancing the resolution of spatial gene expression experiments. BayesSpace clusters a low-dimensional representation of the gene expression matrix, incorporating a spatial prior to encourage neighboring spots to cluster together. The method can enhance the resolution of the low-dimensional representation into “sub-spots”, for which features such as gene expression or cell type composition can be imputed.
BiocIO Implements import()
and export()
standard generics for importing and exporting biological data
formats. import()
supports whole-file as well as chunk-wise
iterative import. The import()
interface optionally provides a
standard mechanism for ‘lazy’ access via filter()
(on row or
element-like components of the file resource), select()
(on
column-like components of the file resource) and collect()
. The
import()
interface optionally provides transparent access to
remote (e.g. via https) as well as local access. Developers can
register a file extension, e.g., .loom
for dispatch from
character-based URIs to specific import()
/ export()
methods
based on classes representing file types, e.g., LoomFile()
.
biocthis This package expands the usethis package with the goal of helping automate the process of creating R packages for Bioconductor or making them Bioconductor-friendly.
bluster Wraps common clustering algorithms in an easily extended S4 framework. Backends are implemented for hierarchical, k-means and graph-based clustering. Several utilities are also provided to compare and evaluate clustering results.
BrainSABER The Allen Institute for Brain Science provides an RNA sequencing (RNA-Seq) data resource for studying transcriptional mechanisms involved in human brain development known as BrainSpan. BrainSABER is an R package that facilitates comparison of user data with the various developmental stages and brain structures found in the BrainSpan atlas by generating dynamic similarity heatmaps for the two data sets. It also provides a self-validating container for user data.
CellaRepertorium Methods to cluster and analyze high-throughput single cell immune cell repertoires, especially from the 10X Genomics VDJ solution. Contains an R interface to CD-HIT (Li and Godzik 2006). Methods to visualize and analyze paired heavy-light chain data. Tests for specific expansion, as well as omnibus oligoclonality under hypergeometric models.
cfDNAPro cfDNA fragment size metrics are important features for utilizing liquid biopsy in tumor early detection, diagnosis, therapy personlization and monitoring. Analyzing and visualizing insert size metrics could be time intensive. This package intends to simplify this exploration process, and it offers two sets of functions for data characterization and data visualization.
ChromSCape ChromSCape - Chromatin landscape profiling for Single Cells - is a ready-to-launch user-friendly Shiny Application for the analysis of single-cell epigenomics datasets (scChIP-seq, scATAC-seq, scCUT&Tag, …) from aligned data to differential analysis & gene set enrichment analysis. It is highly interactive, enables users to save their analysis and covers a wide range of analytical steps: QC, preprocessing, filtering, batch correction, dimensionality reduction, vizualisation, clustering, differential analysis and gene set analysis.
corral Correspondence analysis (CA) is a matrix factorization method, and is similar to principal components analysis (PCA). Whereas PCA is designed for application to continuous, approximately normally distributed data, CA is appropriate for non-negative, count-based data that are in the same additive scale. The corral package implements CA for dimensionality reduction of a single matrix of single-cell data, as well as a multi-table adaptation of CA that leverages data-optimized scaling to align data generated from different sequencing platforms by projecting into a shared latent space. corral utilizes sparse matrices and a fast implementation of SVD, and can be called directly on Bioconductor objects (e.g., SingleCellExperiment) for easy pipeline integration. The package also includes the option to apply CA-style processing to continuous data (e.g., proteomic TOF intensities) with the Hellinger distance adaptation of CA.
customCMPdb This package serves as a query interface for important community collections of small molecules, while also allowing users to include custom compound collections.
CytoTree A trajectory inference toolkit for flow and mass cytometry data. CytoTree is a valuable tool to build a tree-shaped trajectory using flow and mass cytometry data. The application of CytoTree ranges from clustering and dimensionality reduction to trajectory reconstruction and pseudotime estimation. It offers complete analyzing workflow for flow and mass cytometry data.
dasper The aim of dasper is to detect aberrant splicing events from RNA-seq data. dasper will use as input both junction and coverage data from RNA-seq to calculate the deviation of each splicing event in a patient from a set of user-defined controls. dasper uses an unsupervised outlier detection algorithm to score each splicing event in the patient with an outlier score representing the degree to which that splicing event looks abnormal.
DegNorm This package performs degradation normalization in bulk RNA-seq data to improve differential expression analysis accuracy.
densvis Implements the density-preserving modification to t-SNE and UMAP described by Narayan et al. (2020) <doi:10.1101/2020.05.12.077776>. The non-linear dimensionality reduction techniques t-SNE and UMAP enable users to summarise complex high-dimensional sequencing data such as single cell RNAseq using lower dimensional representations. These lower dimensional representations enable the visualisation of discrete transcriptional states, as well as continuous trajectory (for example, in early development). However, these methods focus on the local neighbourhood structure of the data. In some cases, this results in misleading visualisations, where the density of cells in the low-dimensional embedding does not represent the transcriptional heterogeneity of data in the original high-dimensional space. den-SNE and densMAP aim to enable more accurate visual interpretation of high-dimensional datasets by producing lower-dimensional embeddings that accurately represent the heterogeneity of the original high-dimensional space, enabling the identification of homogeneous and heterogeneous cell states. This accuracy is accomplished by including in the optimisation process a term which considers the local density of points in the original high-dimensional space. This can help to create visualisations that are more representative of heterogeneity in the original high-dimensional space.
escape A bridging R package to facilitate gene set enrichment analysis (GSEA) in the context of single-cell RNA sequencing. Using raw count information, Seurat objects, or SingleCellExperiment format, users can perform and visualize GSEA across individual cells.
ExperimentSubset Experiment objects such as the SummarizedExperiment or SingleCellExperiment are data containers for one or more matrix-like assays along with the associated row and column data. Often only a subset of the original data is needed for down-stream analysis. For example, filtering out poor quality samples will require excluding some columns before analysis. The ExperimentSubset object is a container to efficiently manage different subsets of the same data without having to make separate objects for each new subset.
famat Famat is made to collect data about lists of genes and metabolites provided by user, and to visualize it through a Shiny app. Information collected is: - Pathways containing some of the user’s genes and metabolites (obtained using a pathway enrichment analysis). - Direct interactions between user’s elements inside pathways. - Information about elements (their identifiers and descriptions). - Go terms enrichment analysis performed on user’s genes. The Shiny app is composed of: - information about genes, metabolites, and direct interactions between them inside pathways. - an heatmap showing which elements from the list are in pathways (pathways are structured in hierarchies). - hierarchies of enriched go terms using Molecular Function and Biological Process.
FilterFFPE This package finds and filters artificial chimeric reads specifically generated in next-generation sequencing (NGS) process of formalin-fixed paraffin-embedded (FFPE) tissues. These artificial chimeric reads can lead to a large number of false positive structural variation (SV) calls. The required input is an indexed BAM file of a FFPE sample.
flowCut Common techinical complications such as clogging can result in spurious events and fluorescence intensity shifting, flowCut is designed to detect and remove technical artifacts from your data by removing segments that show statistical differences from other segments.
fmrs Provides parameter estimation as well as variable selection in Finite Mixture of Accelerated Failure Time Regression and Finite Mixture of Regression Models. Furthermore, this package provides Ridge Regression and Elastic Net.
FScanR ‘FScanR’ identifies Programmed Ribosomal Frameshifting (PRF) events from BLASTX homolog sequence alignment between targeted genomic/cDNA/mRNA sequences against the peptide library of the same species or a close relative. The output by BLASTX or diamond BLASTX will be used as input of ‘FScanR’ and should be in a tabular format with 14 columns. For BLASTX, the output parameter should be: -outfmt ‘6 qseqid sseqid pident length mismatch gapopen qstart qend sstart send evalue bitscore qframe sframe’. For diamond BLASTX, the output parameter should be: -outfmt 6 qseqid sseqid pident length mismatch gapopen qstart qend sstart send evalue bitscore qframe qframe.
GCSFilesystem Mounting a Google Cloud bucket to a local directory. The files in the bucket can be viewed and read as if they are locally stored. For using the package, you need to install GCSDokan on Windows or gcsfuse on Linux and MacOs.
getDEE2 Digital Expression Explorer 2 (or DEE2 for short) is a repository of processed RNA-seq data in the form of counts. It was designed so that researchers could undertake re-analysis and meta-analysis of published RNA-seq studies quickly and easily. As of April 2020, over 1 million SRA datasets have been processed. This package provides an R interface to access these expression data. More information about the DEE2 project can be found at the project homepage (http://dee2.io) and main publication (https://doi.org/10.1093/gigascience/giz022).
ggtreeExtra ‘ggtreeExtra’ extends the method for mapping and visualizing associated data on phylogenetic tree using ‘ggtree’. These associated data can be mapped to circular layout, fan layout, or other layout tree built by ‘ggtree’ with the grammar of ‘ggplot2’.
GSEAmining Gene Set Enrichment Analysis is a very powerful and interesting computational method that allows an easy correlation between differential expressed genes and biological processes. Unfortunately, although it was designed to help researchers to interpret gene expression data it can generate huge amounts of results whose biological meaning can be difficult to interpret. Many available tools rely on the hierarchically structured Gene Ontology (GO) classification to reduce reundandcy in the results. However, due to the popularity of GSEA many more gene set collections, such as those in the Molecular Signatures Database are emerging. Since these collections are not organized as those in GO, their usage for GSEA do not always give a straightforward answer or, in other words, getting all the meaninful information can be challenging with the currently available tools. For these reasons, GSEAmining was born to be an easy tool to create reproducible reports to help researchers make biological sense of GSEA outputs. Given the results of GSEA, GSEAmining clusters the different gene sets collections based on the presence of the same genes in the leadind edge (core) subset. Leading edge subsets are those genes that contribute most to the enrichment score of each collection of genes or gene sets. For this reason, gene sets that participate in similar biological processes should share genes in common and in turn cluster together. After that, GSEAmining is able to identify and represent for each cluster: - The most enriched terms in the names of gene sets (as wordclouds) - The most enriched genes in the leading edge subsets (as bar plots). In each case, positive and negative enrichments are shown in different colors so it is easy to distinguish biological processes or genes that may be of interest in that particular study.
GSgalgoR A multi-objective optimization algorithm for disease sub-type discovery based on a non-dominated sorting genetic algorithm. The ‘Galgo’ framework combines the advantages of clustering algorithms for grouping heterogeneous ‘omics’ data and the searching properties of genetic algorithms for feature selection. The algorithm search for the optimal number of clusters determination considering the features that maximize the survival difference between sub-types while keeping cluster consistency high.
GWAS.BAYES This package is built to perform GWAS analysis for selfing species. The research related to this package was supported in part by National Science Foundation Award 1853549.
GWENA The development of high-throughput sequencing led to increased use of co-expression analysis to go beyong single feature (i.e. gene) focus. We propose GWENA (Gene Whole co-Expression Network Analysis) , a tool designed to perform gene co-expression network analysis and explore the results in a single pipeline. It includes functional enrichment of modules of co-expressed genes, phenotypcal association, topological analysis and comparison of networks configuration between conditions.
HCAMatrixBrowser The HCAMatrixBrowser queries the HCA matrix endpoint to download expression data and returns a standard Bioconductor object. It uses the LoomExperiment package to serve matrix data that is downloaded as HDF5 loom format.
Herper Many tools for data analysis are not available in R, but are present in public repositories like conda. The Herper package provides a comprehensive set of functions to interact with the conda package managament system. With Herper users can install, manage and run conda packages from the comfort of their R session. Herper also provides an ad-hoc approach to handling external system requirements for R packages. For people developing packages with python conda dependencies we recommend using basilisk (https://bioconductor.org/packages/release/bioc/html/basilisk.html) to internally support these system requirments pre-hoc.
HPAStainR This package is built around the HPAStainR function. The purpose of the HPAStainR function is to query the visual staining data in the Human Protein Atlas to return a table of staining ranked cell types. The function also has multiple arguements to personalize to output as well to include cancer data, csv readable names, modify the confidence levels of the results and more. The other functions exist exlcusively to easily acquire the data required to run HPAStainR.
hummingbird A package for detecting differential methylation. It exploits a Bayesian hidden Markov model that incorporates location dependence among genomic loci, unlike most existing methods that assume independence among observations. Bayesian priors are applied to permit information sharing across an entire chromosome for improved power of detection. The direct output of our software package is the best sequence of methylation states, eliminating the use of a subjective, and most of the time an arbitrary, threshold of p-value for determining significance. At last, our methodology does not require replication in either or both of the two comparison groups.
idpr ‘idpr’ aims to integrate tools for the computational analysis of intrinsically disordered proteins (IDPs) within R. This package is used to identify known characteristics of IDPs for a sequence of interest with easily reported and dynamic results. Additionally, this package includes tools for IDP-based sequence analysis to be used in conjunction with other R packages.
ILoReg ILoReg is a tool for identification of cell populations from scRNA-seq data. In particular, ILoReg is useful for finding cell populations with subtle transcriptomic differences. The method utilizes a self-supervised learning method, called Iteratitive Clustering Projection (ICP), to find cluster probabilities, which are used in noise reduction prior to PCA and the subsequent hierarchical clustering and t-SNE steps. Additionally, functions for differential expression analysis to find gene markers for the populations and gene expression visualization are provided.
infinityFlow Pipeline to analyze and merge data files produced by BioLegend’s LEGENDScreen or BD Human Cell Surface Marker Screening Panel (BD Lyoplates).
Informeasure This package compiles most information measures currently available: mutual information, conditional mutual information, interaction information, partial information decomposition and part mutual information. Using gene expression profile data, all these estimators can be employed to quantify nonlinear dependence between variables in biological regulatory network inference. The first estimator is used to infer bivariate network while the last four estimators are dedicated to analyze trivariate networks.
ISAnalytics In gene therapy, stem cells are modified using viral vectors to deliver the therapeutic transgene and replace functional properties since the genetic modification is stable and inherited in all cell progeny. The retrieval and mapping of the sequences flanking the virus-host DNA junctions allows the identification of insertion sites (IS), essential for monitoring the evolution of genetically modified cells in vivo. A comprehensive toolkit for the analysis of IS is required to foster clonal trackign studies and supporting the assessment of safety and long term efficacy in vivo. This package is aimed at (1) supporting automation of IS workflow, (2) performing base and advance analysis for IS tracking (clonal abundance, clonal expansions and statistics for insertional mutagenesis, etc.), (3) providing basic biology insights of transduced stem cells in vivo.
lefser lefser is an implementation in R of the popular “LDA Effect Size (LEfSe)” method for microbiome biomarker discovery. It uses the Kruskal-Wallis test, Wilcoxon-Rank Sum test, and Linear Discriminant Analysis to find biomarkers of groups and sub-groups.
marr marr (Maximum Rank Reproducibility) is a nonparametric approach that detects reproducible signals using a maximal rank statistic for high-dimensional biological data. In this R package, we implement functions that measures the reproducibility of features per sample pair and sample pairs per feature in high-dimensional biological replicate experiments. The user-friendly plot functions in this package also plot histograms of the reproducibility of features per sample pair and sample pairs per feature. Furthermore, our approach also allows the users to select optimal filtering threshold values for the identification of reproducible features and sample pairs based on output visualization checks (histograms).
megadepth This package provides an R interface to Megadepth by Christopher Wilks available at (https://github.com/ChristopherWilks/megadepth). It is particularly useful for computing the coverage of a set of genomic regions across bigWig or BAM files. With this package, you can build base-pair coverage matrices for regions or annotations of your choice from BigWig files. Megadepth was used to create the raw files provided by https://bioconductor.org/packages/recount3.
MesKit MesKit provides commonly used analysis and visualization modules based on mutational data generated by multi-region sequencing (MRS). This package allows to decipher ITH, infer metastatic routes as well as uncover the underlying process of mutagenesis. Shiny application was also developed for a need of GUI-based analysis. As a handy tool, MesKit can facilitate the understanding of cancer cell evolution and its relevance to cancer therapeutics.
metabCombiner This package aligns LC-HRMS metabolomics datasets acquired from biologically similar specimens analyzed under similar, but not necessarily identical, conditions. Two peak-picked and aligned metabolomics feature tables (consisting of m/z, rt, and per-sample abundance measurements, plus optional identifiers & adduct annotations) are accepted as input. The package outputs a combined table of feature pair alignments, organized into groups of similar m/z, and ranked by a similarity score. Input tables are assumed to be acquired using similar (but not necessarily identical) analytical methods.
metabolomicsWorkbenchR This package provides functions for interfacing with the Metabolomics Workbench RESTful API. Study, compound, protein and gene information can be searched for using the API. Methods to obtain study data in common Bioconductor formats such as SummarizedExperiment and MultiAssayExperiment are also included.
MethReg Epigenome-wide association studies (EWAS) detects a large number of DNA methylation differences, often hundreds of differentially methylated regions and thousands of CpGs, that are significantly associated with a disease, many are located in non-coding regions. Therefore, there is a critical need to better understand the functional impact of these CpG methylations and to further prioritize the significant changes. MethReg is an R package for integrative modeling of DNA methylation, target gene expression and transcription factor binding sites data, to systematically identify and rank functional CpG methylations. MethReg evaluates, prioritizes and annotates CpG sites with high regulatory potential using matched methylation and gene expression data, along with external TF-target interaction databases based on manually curation, ChIP-seq experiments or gene regulatory network analysis.
microbiomeExplorer The MicrobiomeExplorer R package is designed to facilitate the analysis and visualization of marker-gene survey feature data. It allows a user to perform and visualize typical microbiome analytical workflows either through the command line or an interactive Shiny application included with the package. In addition to applying common analytical workflows the application enables automated analysis report generation.
MOFA2 The MOFA2 package contains a collection of tools for running and analysing MOFA models.
MOGAMUN MOGAMUN is a multi-objective genetic algorithm that identifies active modules in a multiplex biological network. This allows analyzing different biological networks at the same time. MOGAMUN is based on NSGA-II (Non-Dominated Sorting Genetic Algorithm, version II), which we adapted to work on networks.
MouseFM This package provides methods for genetic finemapping in inbred mice by taking advantage of their very high homozygosity rate (>95%).
MSEADbi Interface to construct annotation package for MSEA (MSEA.XXX.pb.db). The program design is same as Bioconductor LRBaseDbi or MeSHDbi pacakge, and the usage is also the same as these packages.
msImpute MsImpute is a package for imputation of peptide intensity in proteomics experiments. It additionally contains tools for MAR/MNAR diagnosis and assessment of distortions to the probability distribution of the data post imputation. Currently, msImpute completes missing values by low-rank approximation of the underlying data matrix.
MSPrep Package performs summarization of replicates, filtering by frequency, several different options for imputing missing data, and a variety of options for transforming, batch correcting, and normalizing data.
MSstatsConvert MSstatsConvert provides tools for importing reports of Mass Spectrometry data processing tools into R format suitable for statistical analysis using the MSstats and MSstatsTMT packages.
MSstatsPTM MSstatsPTM provides general statistical methods for quantitative characterization of post-translational modifications (PTMs). Typically, the analysis involves the quantification of PTM sites (i.e., modified residues) and their corresponding proteins, as well as the integration of the quantification results. MSstatsPTM provides functions for summarization, estimation of PTM site abundance, and detection of changes in PTMs across experimental conditions.
MSstatsTMTPTM Tools for Post Translational Modification (PTM) and protein significance analysis in shotgun mass spectrometry-based proteomic experiments with tandem mass tag (TMT) labeling. The functions in this package should be used after PTM/protein summarization. They can be used to both plot the summarized results and model the summarized datasets.
MultiBaC MultiBaC is a strategy to correct batch effects from multiomic datasets distributed across different labs or data acquisition events. MultiBaC is the first Batch effect correction algorithm that dealing with batch effect correction in multiomics datasets. MultiBaC is able to remove batch effects across different omics generated within separate batches provided that at least one common omic data type is included in all the batches considered.
multicrispr This package is for designing Crispr/Cas9 and Prime Editing experiments. It contains functions to (1) define and transform genomic targets, (2) find spacers (4) count offtarget (mis)matches, and (5) compute Doench2016/2014 targeting efficiency. Care has been taken for multicrispr to scale well towards large target sets, enabling the design of large Crispr/Cas9 libraries.
multiGSEA Extracted features from pathways derived from 8 different databases (KEGG, Reactome, Biocarta, etc.) can be used on transcriptomic, proteomic, and/or metabolomic level to calculate a combined GSEA-based enrichment score.
musicatk Mutational signatures are carcinogenic exposures or aberrant cellular processes that can cause alterations to the genome. We created musicatk (MUtational SIgnature Comprehensive Analysis ToolKit) to address shortcomings in versatility and ease of use in other pre-existing computational tools. Although many different types of mutational data have been generated, current software packages do not have a flexible framework to allow users to mix and match different types of mutations in the mutational signature inference process. Musicatk enables users to count and combine multiple mutation types, including SBS, DBS, and indels. Musicatk calculates replication strand, transcription strand and combinations of these features along with discovery from unique and proprietary genomic feature associated with any mutation type. Musicatk also implements several methods for discovery of new signatures as well as methods to infer exposure given an existing set of signatures. Musicatk provides functions for visualization and downstream exploratory analysis including the ability to compare signatures between cohorts and find matching signatures in COSMIC V2 or COSMIC V3.
NanoMethViz NanoMethViz is a toolkit for visualising methylation data from Oxford Nanopore sequencing. It can be used to explore methylation patterns from reads derived from Oxford Nanopore direct DNA sequencing with methylation called by callers including nanopolish, f5c and megalodon. The plots in this package allow the visualisation of methylation profiles aggregated over experimental groups and across classes of genomic features.
ncRNAtools ncRNAtools provides a set of basic tools for handling and analyzing non-coding RNAs. These include tools to access the RNAcentral database and to predict and visualize the secondary structure of non-coding RNAs. The package also provides tools to read, write and interconvert the file formats most commonly used for representing such secondary structures.
nearBynding Provides a pipeline to discern RNA structure at and proximal to the site of protein binding within regions of the transcriptome defined by the user. CLIP protein-binding data can be input as either aligned BAM or peak-called bedGraph files. RNA structure can either be predicted internally from sequence or users have the option to input their own RNA structure data. RNA structure binding profiles can be visually and quantitatively compared across multiple formats.
Nebulosa This package provides a enhanced visualization of single-cell data based on gene-weighted density estimation. Nebulosa recovers the signal from dropped-out features and allows the inspection of the joint expression from multiple features (e.g. genes). Seurat and SingleCellExperiment objects can be used within Nebulosa.
NewWave A model designed for dimensionality reduction and batch effect removal for scRNA-seq data. It is designed to be massively parallelizable using shared objects that prevent memory duplication, and it can be used with different mini-batch approaches in order to reduce time consumption. It assumes a negative binomial distribution for the data with a dispersion parameter that can be both commonwise across gene both genewise.
Omixer Omixer - an R package for multivariate and reproducible randomization with lab-friendly sample layouts. Omixer ensures optimal sample distribution across batches with well-documented methods, and can output intuitive sample sheets for the wet lab if needed.
padma Use multiple factor analysis to calculate individualized pathway-centric scores of deviation with respect to the sampled population based on multi-omic assays (e.g., RNA-seq, copy number alterations, methylation, etc). Graphical and numerical outputs are provided to identify highly aberrant individuals for a particular pathway of interest, as well as the gene and omics drivers of aberrant multi-omic profiles.
pageRank Implemented temporal PageRank analysis as defined by Rozenshtein and Gionis. Implemented multiplex PageRank as defined by Halu et al. Applied temporal and multiplex PageRank in gene regulatory network analysis.
PeacoQC This is a package that includes pre-processing and quality control functions that can remove margin events, compensate and transform the data and that will use PeacoQCSignalStability for quality control. This last function will first detect peaks in each channel of the flowframe. It will remove anomalies based on the IsolationTree function and the MAD outlier detection method. This package can be used for both flow- and mass cytometry data.
periodicDNA This R package helps the user identify k-mers (e.g. di- or tri-nucleotides) present periodically in a set of genomic loci (typically regulatory elements). The functions of this package provide a straightforward approach to find periodic occurrences of k-mers in DNA sequences, such as regulatory elements. It is not aimed at identifying motifs separated by a conserved distance; for this type of analysis, please visit MEME website.
PhosR PhosR is a package for the comprenhensive analysis of phosphoproteomic data. There are two major components to PhosR: processing and downstream analysis. PhosR consists of various processing tools for phosphoproteomics data including filtering, imputation, normalisation, and functional analysis for inferring active kinases and signalling pathways.
pipeComp A simple framework to facilitate the
comparison of pipelines involving various steps and parameters. The
pipelineDefinition
class represents pipelines as, minimally, a
set of functions consecutively executed on the output of the
previous one, and optionally accompanied by step-wise evaluation
and aggregation functions. Given such an object, a set of
alternative parameters/methods, and benchmark datasets, the
runPipeline
function then proceeds through all combinations
arguments, avoiding recomputing the same step twice and compiling
evaluations on the fly to avoid storing potentially large
intermediate data.
POMA POMA introduces a structured, reproducible and easy-to-use workflow for the visualization, pre-processing, exploratory and statistical analysis of mass spectrometry data. The main aim of POMA is to enable a flexible data cleaning and statistical analysis processes in one comprehensible and user-friendly R package. This package also has a Shiny app version that implements all POMA functions. See https://github.com/pcastellanoescuder/POMAShiny.
preciseTAD preciseTAD provides functions to predict the location of boundaries of topologically associated domains (TADs) and chromatin loops at base-level resolution. As an input, it takes BED-formatted genomic coordinates of domain boundaries detected from low-resolution Hi-C data, and coordinates of high-resolution genomic annotations from ENCODE or other consortia. preciseTAD employs several feature engineering strategies and resampling techniques to address class imbalance, and trains an optimized random forest model for predicting low-resolution domain boundaries. Translated on a base-level, preciseTAD predicts the probability for each base to be a boundary. Density-based clustering and scalable partitioning techniques are used to detect precise boundary regions and summit points. Compared with low-resolution boundaries, preciseTAD boundaries are highly enriched for CTCF, RAD21, SMC3, and ZNF143 signal and more conserved across cell lines. The pre-trained model can accurately predict boundaries in another cell line using CTCF, RAD21, SMC3, and ZNF143 annotation data for this cell line.
proActiv Most human genes have multiple promoters that control the expression of different isoforms. The use of these alternative promoters enables the regulation of isoform expression pre-transcriptionally. Alternative promoters have been found to be important in a wide number of cell types and diseases. proActiv is an R package that enables the analysis of promoters from RNA-seq data. proActiv uses aligned reads as input, and generates counts and normalized promoter activity estimates for each annotated promoter. In particular, proActiv accepts junction files from TopHat2 or STAR or BAM files as inputs. These estimates can then be used to identify which promoter is active, which promoter is inactive, and which promoters change their activity across conditions.
QFeatures The QFeatures infrastructure enables the management and processing of quantitative features for high-throughput mass spectrometry assays. It provides a familiar Bioconductor user experience to manages quantitative data across different assay levels (such as peptide spectrum matches, peptides and proteins) in a coherent and tractable format.
RadioGx Computational tool box for radio-genomic analysis which integrates radio-response data, radio-biological modelling and comprehensive cell line annotations for hundreds of cancer cell lines. The ‘RadioSet’ class enables creation and manipulation of standardized datasets including information about cancer cells lines, radio-response assays and dose-response indicators. Included methods allow fitting and plotting dose-response data using established radio-biological models along with quality control to validate results. Additional functions related to fitting and plotting dose response curves, quantifying statistical correlation and calculating area under the curve (AUC) or survival fraction (SF) are included. For more details please see the included documentation, references, as well as: Manem, V. et al (2018) <doi:10.1101/449793>.
rebook Provides utilities to re-use content across chapters of a Bioconductor book. This is mostly based on functionality developed while writing the OSCA book, but generalized for potential use in other large books with heavy compute. Also contains some functions to assist book deployment.
recount3 Explore and download data from the recount project available at https://jhubiostatistics.shinyapps.io/recount3/. Using the recount3 package you can download RangedSummarizedExperiment objects at the gene, exon or exon-exon junctions level, the raw counts, the phenotype metadata used, the urls to the sample coverage bigWig files. The RangedSummarizedExperiment objects can be used by different packages for performing differential expression analysis. Using data from the recount3 project you can perform annotation-agnostic differential expression analyses as described at http://doi.org/TODO.
recountmethylation Access cross-study compilations of DNA methylation array databases. Database files can be downloaded and accessed using provided functions. Background about database file types (HDF5 and HDF5-SummarizedExperiment), SummarizedExperiment classes, and examples for data handling, validation, and analyses, can be found in the package vignettes. Note the disclaimer on package load, and consult the main manuscript for further info.
RegEnrich This package is a pipeline to identify the key gene regulators in a biological process, for example in cell differentiation and in cell development after stimulation. There are four major steps in this pipeline: (1) differential expression analysis; (2) regulator-target network inference; (3) enrichment analysis; and (4) regulators scoring and ranking.
ResidualMatrix Provides delayed computation of a matrix of residuals after fitting a linear model to each column of an input matrix. Also supports partial computation of residuals where selected factors are to be preserved in the output matrix. Implements a number of efficient methods for operating on the delayed matrix of residuals, most notably matrix multiplication and calculation of row/column sums or means.
Rfastp Rfastp is an R wrapper of fastp developed in c++. fastp performs quality control for fastq files. including low quality bases trimming, polyX trimming, adapter auto-detection and trimming, paired-end reads merging, UMI sequence/id handling. Rfastp can concatenate multiple files into one file (like shell command cat) and accept multiple files as input.
RIPAT RIPAT is developed as an R package for retroviral integration sites annotation and distribution analysis. RIPAT needs local alignment results from BLAST and BLAT. Specific input format is depicted in RIPAT manual. RIPAT provides RV integration pattern analysis result as forms of R objects, excel file with multiple sheets and plots.
rnaEditr RNAeditr analyzes site-specific RNA editing events, as well as hyper-editing regions. The editing frequencies can be tested against binary, continuous or survival outcomes. Multiple covariate variables as well as interaction effects can also be incorporated in the statistical models.
RnaSeqSampleSize RnaSeqSampleSize package provides a sample size calculation method based on negative binomial model and the exact test for assessing differential expression analysis of RNA-seq data. It controls FDR for multiple testing and utilizes the average read count and dispersion distributions from real data to estimate a more reliable sample size. It is also equipped with several unique features, including estimation for interested genes or pathway, power curve visualization, and parameter optimization.
rsemmed A programmatic interface to the Semantic MEDLINE database. It provides functions for searching the database for concepts and finding paths between concepts. Path searching can also be tailored to user specifications, such as placing restrictions on concept types and the type of link between concepts. It also provides functions for summarizing and visualizing those paths.
Rtpca R package for performing thermal proximity co-aggregation analysis with thermal proteome profiling datasets to analyse protein complex assembly and (differential) protein-protein interactions across conditions.
sangeranalyseR This package builds on sangerseqR to allow users to create contigs from collections of Sanger sequencing reads. It provides a wide range of options for a number of commonly-performed actions including read trimming, detecting secondary peaks, and detecting indels using a reference sequence. All parameters can be adjusted interactively either in R or in the associated Shiny applications. There is extensive online documentation, and the package can outputs detailed HTML reports, including chromatograms.
SCATE SCATE is a software tool for extracting and enhancing the sparse and discrete Single-cell ATAC-seq Signal. Single-cell sequencing assay for transposase-accessible chromatin (scATAC-seq) is the state-of-the-art technology for analyzing genome-wide regulatory landscapes in single cells. Single-cell ATAC-seq data are sparse and noisy, and analyzing such data is challenging. Existing computational methods cannot accurately reconstruct activities of individual cis-regulatory elements (CREs) in individual cells or rare cell subpopulations. SCATE was developed to adaptively integrate information from co-activated CREs, similar cells, and publicly available regulome data and substantially increase the accuracy for estimating activities of individual CREs. We demonstrate that SCATE can be used to better reconstruct the regulatory landscape of a heterogeneous sample.
scCB2 scCB2 is an R package implementing CB2 for distinguishing real cells from empty droplets in droplet-based single cell RNA-seq experiments (especially for 10x Chromium). It is based on clustering similar barcodes and calculating Monte-Carlo p-value for each cluster to test against background distribution. This cluster-level test outperforms single-barcode-level tests in dealing with low count barcodes and homogeneous sequencing library, while keeping FDR well controlled.
scDataviz In the single cell World, which includes flow cytometry, mass cytometry, single-cell RNA-seq (scRNA-seq), and others, there is a need to improve data visualisation and to bring analysis capabilities to researchers even from non-technical backgrounds. scDataviz attempts to fit into this space, while also catering for advanced users. Additonally, due to the way that scDataviz is designed, which is based on SingleCellExperiment, it has a ‘plug and play’ feel, and immediately lends itself as flexibile and compatibile with studies that go beyond scDataviz. Finally, the graphics in scDataviz are generated via the ggplot engine, which means that users can ‘add on’ features to these with ease.
SCFA Subtyping via Consensus Factor Analysis (SCFA) can efficiently remove noisy signals from consistent molecular patterns in multi-omics data. SCFA first uses an autoencoder to select only important features and then repeatedly performs factor analysis to represent the data with different numbers of factors. Using these representations, it can reliably identify cancer subtypes and accurately predict risk scores of patients.
scp Utility functions for manipulating, processing, and analyzing mass spectrometry-based single-cell proteomics (SCP) data. The package is an extension to the ‘QFeatures’ package designed for SCP applications.
scRepertoire scRepertoire was built to process data derived from the 10x Genomics Chromium Immune Profiling for both T-cell receptor (TCR) and immunoglobulin (Ig) enrichment workflows and subsequently interacts with the popular Seurat and SingleCellExperiment R packages.
scuttle Provides basic utility functions for performing single-cell analyses, focusing on simple normalization, quality control and data transformations. Also provides some helper functions to assist development of other packages.
SeqGate Filtering of lowly expressed features (e.g. genes) is a common step before performing statistical analysis, but an arbitrary threshold is generally chosen. SeqGate implements a method that rationalize this step by the analysis of the distibution of counts in replicate samples. The gate is the threshold above which sequenced features can be considered as confidently quantified.
simplifyEnrichment A new method (binary cut) is proposed to effectively cluster GO terms into groups from the semantic similarity matrix. Summaries of GO terms in each cluster are visualized by word clouds.
snifter Provides an R wrapper for the implementation of FI-tSNE from the python package openTNSE. See Poličar et al. (2019) <doi:10.1101/731877> and the algorithm described by Linderman et al. (2018) <doi:10.1038/s41592-018-0308-4>.
SpatialDecon Using spatial or bulk gene expression data, estimates abundance of mixed cell types within each observation. Based on “Advances in mixed cell deconvolution enable quantification of cell types in spatially-resolved gene expression data”, Danaher (2020). Designed for use with the NanoString GeoMx platform, but applicable to any gene expression data.
SpatialExperiment Defines S4 classes for storing data for spatial experiments. Main examples are reported by using seqFISH and 10x-Visium Spatial Gene Expression data. This includes specialized methods for storing, retrieving spatial coordinates, 10x dedicated parameters and their handling.
spatialHeatmap The spatialHeatmap package provides functionalities for visualizing cell-, tissue- and organ-specific data of biological assays by coloring the corresponding spatial features defined in anatomical images according to a numeric color key.
Spectra The Spectra package defines an efficient infrastructure for storing and handling mass spectrometry spectra and functionality to subset, process, visualize and compare spectra data. It provides different implementations (backends) to store mass spectrometry data. These comprise backends tuned for fast data access and processing and backends for very large data sets ensuring a small memory footprint.
SPsimSeq SPsimSeq uses a specially designed exponential family for density estimation to constructs the distribution of gene expression levels from a given real RNA sequencing data (single-cell or bulk), and subsequently simulates a new dataset from the estimated marginal distributions using Gaussian-copulas to retain the dependence between genes. It allows simulation of multiple groups and batches with any required sample size and library size.
systemPipeShiny systemPipeShiny (SPS) extends the widely used systemPipeR (SPR) workflow environment with a versatile graphical user interface provided by a Shiny App. This allows non-R users, such as experimentalists, to run many systemPipeR’s workflow designs, control, and visualization functionalities interactively without requiring knowledge of R. Most importantly, SPS has been designed as a general purpose framework for interacting with other R packages in an intuitive manner. Like most Shiny Apps, SPS can be used on both local computers as well as centralized server-based deployments that can be accessed remotely as a public web service for using SPR’s functionalities with community and/or private data. The framework can integrate many core packages from the R/Bioconductor ecosystem. Examples of SPS’ current functionalities include: (a) interactive creation of experimental designs and metadata using an easy to use tabular editor or file uploader; (b) visualization of workflow topologies combined with auto-generation of R Markdown preview for interactively designed workflows; (d) access to a wide range of data processing routines; (e) and an extendable set of visualization functionalities. Complex visual results can be managed on a ‘Canvas Workbench’ allowing users to organize and to compare plots in an efficient manner combined with a session snapshot feature to continue work at a later time. The present suite of pre-configured visualization examples. The modular design of SPR makes it easy to design custom functions without any knowledge of Shiny, as well as extending the environment in the future with contributions from the community.
TADCompare TADCompare is an R package designed to identify and characterize differential Topologically Associated Domains (TADs) between multiple Hi-C contact matrices. It contains functions for finding differential TADs between two datasets, finding differential TADs over time and identifying consensus TADs across multiple matrices. It takes all of the main types of HiC input and returns simple, comprehensive, easy to analyze results.
tidySingleCellExperiment tidySingleCellExperiment is an adapter that abstracts the ‘SingleCellExperiment’ container in the form of tibble and allows the data manipulation, plotting and nesting using ‘tidyverse’
tidySummarizedExperiment tidySummarizedExperiment is an adapter that abstracts the ‘SingleCellExperiment’ container in the form of tibble and allows the data manipulation, plotting and nesting using ‘tidyverse’
TileDBArray Implements a DelayedArray backend for reading and writing dense or sparse arrays in the TileDB format. The resulting TileDBArrays are compatible with all Bioconductor pipelines that can accept DelayedArray instances.
TimiRGeN TimiRGeN (Time Incorporated miR-mRNA Generation of Networks) is a novel R package which functionally analyses and integrates time course miRNA-mRNA differential expression data. This tool can generate small networks within R or export results into cytoscape or pathvisio for more detailed network construction and hypothesis generation. This tool is created for researchers that wish to dive deep into time series multi-omic datasets. TimiRGeN goes further than many other tools in terms of data reduction. Here, potentially hundreds of thousands of potential miRNA-mRNA interactions can be whittled down into a handful of high confidence miRNA-mRNA interactions effecting a signalling pathway, across a time course.
tomoda This package provides many easy-to-use methods to analyze and visualize tomo-seq data. The tomo-seq technique is based on cryosectioning of tissue and performing RNA-seq on consecutive sections. (Reference: Kruse F, Junker JP, van Oudenaarden A, Bakkers J. Tomo-seq: A method to obtain genome-wide expression data with spatial resolution. Methods Cell Biol. 2016;135:299-307. doi:10.1016/bs.mcb.2016.01.006) The main purpose of the package is to find zones with similar transcriptional profiles and spatially expressed genes in a tomo-seq sample. Several visulization functions are available to create easy-to-modify plots.
ToxicoGx Contains a set of functions to perform large-scale analysis of toxicogenomic data, providing a standardized data structure to hold information relevant to annotation, visualization and statistical analysis of toxicogenomic data.
transomics2cytoscape transomics2cytoscape generates a file for 3D transomics visualization by providing input that specifies the IDs of multiple KEGG pathway layers, their corresponding Z-axis heights, and an input that represents the edges between the pathway layers. The edges are used, for example, to describe the relationships between kinase on a pathway and enzyme on another pathway. This package automates creation of a transomics network as shown in the figure in Yugi.2014 (https://doi.org/10.1016/j.celrep.2014.07.021) using Cytoscape automation (https://doi.org/10.1186/s13059-019-1758-4).
UMI4Cats UMI-4C is a technique that allows characterization of 3D chromatin interactions with a bait of interest, taking advantage of a sonication step to produce unique molecular identifiers (UMIs) that help remove duplication bias, thus allowing a better differential comparsion of chromatin interactions between conditions. This package allows processing of UMI-4C data, starting from FastQ files provided by the sequencing facility. It provides two statistical methods for detecting differential contacts and includes a visualization function to plot integrated information from a UMI-4C assay.
uncoverappLib a Shiny application containing a suite of graphical and statistical tools to support clinical assessment of low coverage regions.It displays three web pages each providing a different analysis module: Coverage analysis, calculate AF by allele frequency app and binomial distribution.
velociraptor This package provides Bioconductor-friendly wrappers for RNA velocity calculations in single-cell RNA-seq data. We use the basilisk package to manage Conda environments, and the zellkonverter package to convert data structures between SingleCellExperiment (R) and AnnData (Python). The information produced by the velocity methods is stored in the various components of the SingleCellExperiment class.
VERSO Mutations that rapidly accumulate in viral genomes during a pandemic can be used to track the evolution of the virus and, accordingly, unravel the viral infection network. To this extent, sequencing samples of the virus can be employed to estimate models from genomic epidemiology and may serve, for instance, to estimate the proportion of undetected infected people by uncovering cryptic transmissions, as well as to predict likely trends in the number of infected, hospitalized, dead and recovered people. VERSO is an algorithmic framework that processes variants profiles from viral samples to produce phylogenetic models of viral evolution. The approach solves a Boolean Matrix Factorization problem with phylogenetic constraints, by maximizing a log-likelihood function. VERSO includes two separate and subsequent steps; in this package we provide an R implementation of VERSO STEP 1.
VplotR The pattern of digestion and protection from DNA nucleases such as DNAse I, micrococcal nuclease, and Tn5 transposase can be used to infer the location of associated proteins. This package contains useful functions to analyze patterns of paired-end sequencing fragment density. VplotR facilitates the generation of V-plots and footprint profiles over single or aggregated genomic loci of interest.
wpm This is a shiny application for creating well-plate plans. It uses a backtracking-inspired algorithm to place samples on plates based on specific neighborhood constraints.
zellkonverter Provides methods to convert between Python AnnData objects and SingleCellExperiment objects. These are primarily intended for use by downstream Bioconductor packages that wrap Python methods for single-cell data analysis. It also includes functions to read and write H5AD files used for saving AnnData objects to disk.
There are 9 new data experiment packages in this release of Bioconductor.
celldex Provides a collection of reference expression datasets with curated cell type labels, for use in procedures like automated annotation of single-cell data or deconvolution of bulk RNA-seq.
clustifyrdatahub References made from external single-cell mRNA sequencing data sets, stored as average gene expression matrices. For use with clustifyr https://bioconductor.org/packages/clustifyr to assign cell type identities.
DropletTestFiles Assorted files generated from droplet-based single-cell protocols, to be used for testing functions in DropletUtils. Primarily intended for storing files that directly come out of processing pipelines like 10X Genomics’ CellRanger software, prior to the formation of a SingleCellExperiment object. Unlike other packages, this is not designed to provide objects that are immediately ready for analysis.
FieldEffectCrc Processed RNA-seq data for 1,139 human primary colorectal tissue samples across three phenotypes, including tumor, normal adjacent-to-tumor, and healthy, available as Synapse ID syn22237139 on synapse.org. Data have been parsed into SummarizedExperiment objects available via ExperimentHub to facilitate reproducibility and extension of results from Dampier et al. (PMCID: PMC7386360, PMID: 32764205).
MethylSeqData Base-level (i.e. cytosine-level) counts for a collection of public bisulfite-seq datasets (e.g., WGBS and RRBS), provided as SummarizedExperiment objects with sample- and base-level metadata.
NanoporeRNASeq The NanoporeRNASeq package contains long read RNA-Seq data generated using Oxford Nanopore Sequencing. The data consists of 6 samples from two human cell lines (K562 and MCF7) that were generated by the SG-NEx project. Each of these cell lines has three replicates, with 1 direct RNA sequencing data and 2 cDNA sequencing data. Reads are aligned to chromosome 22 (Grch38) and stored as bam files. The original data is from the SG-NEx project.
SCATEData SCATEData is an ExperimentHub package for SCATE which is a software tool for extracting and enhancing the sparse and discrete Single-cell ATAC-seq Signal.
timecoursedata This data package contains timecourse gene expression data sets. The first dataset, from Shoemaker et al, consists of microarray samples from lung tissue of mice exposed to different influenzy strains from 14 timepoints. The two other datasets are leaf and root samples from sorghum crops exposed to pre- and post-flowering drought stress and a control condition, sampled across the plants lifetime.
TMExplorer This package provides a tool to search and download a collection of tumour microenvironment single-cell RNA sequencing datasets and their metadata. TMExplorer aims to act as a single point of entry for users looking to study the tumour microenvironment at the single cell level. Users can quickly search available datasets using the metadata table and then download the ones they are interested in for analysis.
There are two new annotation packages in this release of Bioconductor.
metaboliteIDmapping The package provides a comprehensive mapping table of nine different Metabolite ID formats and their common name. The data has been collected and merged from four publicly available source, including HMDB, Comptox Dashboard, ChEBI, and the graphite Bioconductor R package.
geneplast.data The package geneplast.data provides an interface for obtaining input data used in the analyses pipelines from geneplast package. Objects containing species, phylogenetic trees, and orthology information of eukaryotes from different orthologous databases are provided
There is 1 new workflow package in this release of Bioconductor.
There are 2 online books in this release of Bioconductor. While the OSCA book has been around for a longer period of time than this release, this is the first release where the book is being hosted, built. and checked by the Bioconductor builders.
OSCA This is the website for “Orchestrating Single-Cell Analysis with Bioconductor”, a book that teaches users some common workflows for the analysis of single-cell RNA-seq data (scRNA-seq). This book will teach you how to make use of cutting-edge Bioconductor tools to process, analyze, visualize, and explore scRNA-seq data. Additionally, it serves as an online companion for the manuscript “Orchestrating Single-Cell Analysis with Bioconductor”.
SingleRBook This book covers the use of SingleR, one implementation of an automated annotation method. If you want a survey of different annotation methods - this book is not for you. If you want to create hand-crafted cluster definitions - this book is not for you. (Read the other one instead.) If you want to use the pre-Bioconductor version of the package - this book is not for you. But if you’re tired of manually annotating your single-cell data and you want to do something better with your life, then read on.
Changes in version 1.37.2
Changes in version 1.37.3
fix specification of link for fct with different name help page
Changes in version 1.37.2
use Imports rather than Depends + use roxygen2 for documentation
use Authors@R
replace toptable (deprecated in limma 3.36.0) by limma:::.topTableT
Changes in version 1.37.1
spectralMap: fix legend win-32
Changes in version 1.37.1
use Imports rather than Depends + use roxygen2 for documentation
use Authors@R
add vignette, examples
Changes in version 1.37.1
use Imports rather than Depends + use roxygen2 for documentation
use Authors@R
add vignette
Changes in version 1.37.1
use Imports rather than Depends + use roxygen2 for documentation
use Authors@R
add vignette
Changes in version 1.37.1
use Imports rather than Depends + use roxygen2 for documentation
use Authors@R
add vignette
Changes in version 2.1.0
Changes in version 1.7.1
BUG FIXED
Changes in version 0.99.0 (2020-09-03)
Changes in version 1.5.2
Changes in version 1.2.3 (2020-06-06)
Fixed bugs.
Compatible with new version of dplyr,data.tables
Changes in version 1.2.1 (2020-04-20)
Fixed bugs.
Added SOMA functions.
Changes in version 2.99.5 (2020-10-14)
norm_pqn_diagnostic$norm_factor used in tutorial instead of plot it
Changes in version 2.99.4 (2020-09-28)
Suppressed other warnings of plot_interactive function
Changes in version 2.99.3 (2020-09-21)
Commented out code removed
Changes in version 2.99.2 (2020-08-26)
Modified introduction to alpsnmr vignette and some tests to work with reduced demo dataset
Changes in version 2.99.1 (2020-08-25)
Modified examples to avoid create files in main package folder
Changes in version 2.99.0 (2020-08-24)
Minor modifications for bioconductor submision
Changes in version 2.5.9002 (2020-05-25)
Added permutation test and permutation test plot to nmr_data_analysis
Changes in version 2.4.9002 (2020-05-13)
Changes to pass checks for R4
Changes in version 2.3.3.9002
nmr_diagnose is deprecated. Since nmr_diagnose was only used for getting extra normalization information, it was been replaced with nmr_normalize_extra_info that offers a less confusing name.
Changes in version 2.3.3.9001
Update of README file
Changes in version 2.3.3
New functions to apply machine learning to proccessed datasets
Changes in version 2.3.2
New files_to_rDolphin function
Changes in version 2.3.1.9000
Rename package from NIHSnmr to AlpsNMR
Changes in version 2.3.1
Last version form Sergio (changes not significant since 2.3.0)
Changes in version 2.3.0
Minor bug fixes
Changes in version 2.2.0
Minor bug fixes
Changes in version 2.1.0
nmr_dataset_peak_table object for peak detection results
Changes in version 2.0.0
Too many changes to be listed here. Check the vignette for a summary of all the features. Use browseVignettes(“NIHSnmr”).
Changes in version 1.2.0
Breaking changes
Rename injection_id to NMRExperiment.
nmr_dataset_load and nmr_dataset_save now use readRDS and saveRDS instead of load and save. This is the right approach to serialize single R objects. If you need a script to convert previously saved datasets (created using nmr_dataset_save) please use NIHSnmr:::nmr_dataset_load_old_and_save(“your_old_file.RData”, “your_old_file.RDS”) to convert the files. Sorry for the inconvenience, but the sooner we fix this the better.
filter to select a subset of samples from an nmr_dataset object has been adapted to dplyr >= 0.7.4. Unless you used the .dots argument in your calls there is no need to change anything. This means we now use a tidy evaluation syntax for filter.
nmr_get_metadata() returns always a data frame / tibble, even when only a single column is requested. It also always includes the “NMRExperiment” column.
nmr_dataset object has two tables metadata and metadata_ext. The metadata_ext table includes all the metadata we add with nmr_add_metadata while metadata has the internal metadata (acquisition parameters, etc). Please use nmr_get_metadata(nmr_dataset) instead of nmr_dataset$metadata.
Other changes
Remove workaround to dplyr issue: https://github.com/tidyverse/dplyr/issues/2203 (Sergio Oller reported and fixed the issue, dplyr-0.7.0 is fixed)
The Bruker title file has quite a free format definition. A title file can contain lines like “Field value” or “Field value ;” or simply “value”. The heuristics to parse the title file have been improved.
Depend on tidyr 0.8.1. tidyr 0.8.0 had a bug that we reported (and for which we also provided a fix): https://github.com/tidyverse/tidyr/pull/419
nmr_get_metadata gives a warning if the user asks for metadata columns that are missing.
New nmr_integrate_regions function.
nmr_normalize accepts pqn normalization.
Changes in version 0.99.5 (2020-10-19)
Update README
Changes in version 0.99.4 (2020-09-26)
Update README
Changes in version 0.99.3 (2020-09-13)
Using the GlobalPatterns dataset in the examples
Changes in version 0.99.2 (2020-09-05)
Integrating with phyloseq-class experiment-level object
Changes in version 0.99.1 (2020-08-23)
Addressed reviewer’s comments
Changes in version 0.99.0 (2020-08-10)
Submitted to Bioconductor
Changes in version 2.21.0
BUG FIX
(2.21.5) Fix documentation for setting AnnotationHubOptions
(2.21.3) Fix printing of proxy when present
USER-VISIBLE MODIFICATIONS
(2.21.6) Make internet connection test less stringent
(2.21.4) Add link to github for reporting issues
(2.21.2) Update to reference hubs@bioconductor.org for help
(2.21.1) Update .tidyGRanges to account for incorrect or missing genomes
Changes in version 1.19.0
INTERNAL BUG CORRECTION
1.19.2 Update Metadata from Ensembl function to use GenomeInfoDb:::fetch_species_index_from_Ensembl_FTP instead of parsing the file path
1.19.1 misplaced ! clause
Changes in version 1.16.0
USER-FACING CHANGES
BUGFIXES
Changes in version 1.2.0
NEW FEATURES
(v 1.1.3) introduce .deprecated flag in operations() / tags(); don’t include deprecated APIs by default; warn on use of deprecated APIs.
(v 1.1.4) add repositories() to return binary (if available), Bioconductor, and CRAN repository paths.
(v 1.1.6) provide md5sum as check on service version.
(v 1.1.9) add avfiles_*() for managing workspace bucket files.
(v 1.1.15) add avtable_import_set() to create subsets of tables, following the Terra data model.
(v 1.1.16) add avruntimes(), avworkspace_jobs() to query for runtimes and jobs associated with the active billing account.
(v 1.1.17) add avdisks() to query for persistent disks associate with the active billing account.
(v 1.1.21) add avworkflow_*() for interacting with workflow jobs and outputs.
Changes in version 0.0.12
pass CMD check and BiocCheck
Changes in version 0.0.11
removes browse_reck parameters, encapsulates authentication better
Changes in version 0.0.10
New parameter to browse_reck() that defaults to NOT running bq_auth explicitly. Now only one authentication per session is performed if do_auth is FALSE
Changes in version 0.0.9
Plots in plot tab are now plotly for pointwise segmented display, and simple cumulative display
Changes in version 0.0.7
Changes in version 0.0.10
Add ‘best practices’ and rationale for Rmarkdown-to-jupyter notebook conversion.
Changes in version 0.0.9
as_workspace(…, create = FALSE, update=FALSE) now evaluates code, silently.
Changes in version 0.0.8
Add R / Bioconductor version to dashboard
Changes in version 0.0.7
Revise Rmd-to-ipynb work flow
Insert metadata to use the R kernel. jupytext can do this more elegantly, but does from .md renders code chunks and pre-formatted rather than evaluation cells, and from .Rmd does not process markdown well enough, e.g., not suppporting [foo][]-style links when the definition is elsewhere in the document.
Changes in version 0.0.6
Added a NEWS.md file to track changes to the package.
Extensive interface renaming
Changes in version 1.3.3 (2020-07-20)
Fixed hg38_REF.RData.
Changes in version 1.3.2 (2020-07-20)
Updated the CITATION.
Changes in version 1.3.1 (2020-07-19)
Fixed the interval issues in hg38_REF.RData and mm10_REF.RData.
Updated the CITATION.
Changes in version 1.6.7 (2020-10-22)
The following plots are now deprecated
.clustering.log2fcSign.all-zoom.pdf
.clustering.log2fc.all-zoom.pdf
Fix bugs
Changes in version 1.6.6 (2020-10-21)
Convert new MaxQuant format of PTMs to the old format
MSstats messages are not displayed by default when using artmsQuantification. The user can enable MSstats messages by selecting “display_msstats = TRUE”
Prevent artmsWriteConfigYamlFile() from overwriting an existing configuration file unless the user allows it (overwrite = TRUE)
printPDF now available in all functions printing plots to pdf, which means that notebooks can be used and print all plots. Default is still printPDF = TRUE
Fix bugs
Changes in version 1.6.5 (2020-05-20)
Fix ggplot warnings (caused by NA values)
Fix artmsAnalysisQuantification reproducibility plots
Improves artmsQualityControlEvidenceBasic() correlation matrix clustered plot
Fix pca01.pdf plot
New pca04.pdf plot (dot plot)
artmsAnalysisQuantifications check point: check if sufficient data is available
Changes in version 1.6.4 (2020-05-12)
Fix Quality Control functions to handle a small number of runs (less than 5)
New argument “printPDF” for artmsQualityControlSummaryExtended, to select whether to print plots to PDFs (default = TRUE)
Vignette: example plots added
Changes in version 1.6.3 (2020-05-06)
Bug Fixes affecting artmsAnalysisQuantifications()
Changes in version 1.6.2 (2020-05-05)
Fix NEWS formatting
Update vignette with AC options
Changes in version 1.6.1 (2020-04-29)
Fix NEWS formatting
Update vignette with AC options
Changes in version 1.99.3
NEW FUNCTIONS AND FUNCTIONALITIES
New parameters for gbCounts and jCounts functions:
libType: to specify single end (“SE”) or paired end (“PE”) library
strandMode:
2: strand of the pair is strand of its last alignment.
Changes in version 1.99.1
NEW FUNCTIONS AND FUNCTIONALITIES
For counting: gbCounts and jCounts. We add library type and strand-specificity parameters.
For DU estimation: DUreport.norm and DUreport.offset
For prepare DU reports: filterSignals, gbDUreport, integrateSignals, jDUreport, splicingReport and junctionsPJU
For printing reports: exportIntegratedSignals, writeJDU and writeSplicingReport
FUNCTIONS DEPRECATED
loadBAM: will be replaced by gbCounts. Bams files are proccesed one by one, according target object. It improves running time and memory usage
readCounts: it is replaced by gbCounts
AsDiscover: it is replaced by jCounts
DUreport: it is replaced by gbDUreport and jDUreport
mergeBinDUAS: has no direct replacement.
plotGenomicRegions: has not direct replacement. There are new functions for exportiing results into HTML pages.
Changes in version 1.7.1 (2020-10-23)
Genome viewer plots will now show the forward strand above the reverse strand, and reading frames will now be laid out in 1 through 6 order moving down the genome viewer (before it was reversed)
Changes in version 1.7.0 (2020-10-21)
Can now toggle interactivity of the genome viewer when plotting Assessment objects
Can now zoom into an initial range with the genome viewer when plotting Assessment objects
Documented the genome viewer in the plot.Assessment man page
Added a genome viewer example to the vignette
Fixed a bug that was causing an error when users attempted to zoom out ten-fold with the genome viewer plot
Changes in version 1.13.9
fix the issue that plotCorrelation heatmap is scaled by row.
Changes in version 1.13.8
throw an error if not enought nucleosome free read nor mononucleosome reads for training.
Changes in version 1.13.7
fix a bug introduced by matchPWM by paste ^ and $ into exclude sequence name.
Changes in version 1.13.6
update documentation of plotFootprints.
Changes in version 1.13.4
fix a formular for TSSE score.
Changes in version 1.13.3
fix a bug the after shift, the index is not changed.
Changes in version 1.13.2
change the normalization method by library size for factorFootprints for user defined group samples.
Changes in version 1.13.1
Add documentation to decribe the format of bindingSites for factorFootprints.
Changes in version 1.3.0 (2020-09-24)
Updated the required version of dependencies
Added flag for plot peaks courtesy of John Bouranis
Changes in version 1.4.1
Changes in version 2.1.16 (2020-10-22)
Updates .BASiCS_MCMC_Start
to use different starting values when an
empirical Bayes prior is assigned to mu
Adds log_scale
parameter to .EmpiricalBayesMu
Fixes small bug in .BASiCS_MCMC_Start
Updates unit tests linked to the change in .BASiCS_MCMC_Start
Adds fixed seeds to test_divide_and_conquer.R
Changes in version 2.1.14 (2020-10-08)
Add support for divide and conquer inference with
BASiCS_DivideAndConquer
function. Add support for this function to BASiCS_MCMC
Add BASiCS_MockSCE
function to create a SingleCellExperiment
object with arbitrary dimensions.
Fix Makevars warning relating to PKG_CXXFLAGS
Changes in version 2.1.13 (2020-10-05)
Add PriorParam argument to BASiCS_MCMC
Changes in version 2.1.12 (2020-10-01)
Remove unused DelayedArray call from tests
Changes in version 2.1.11 (2020-09-30)
Updated documentation for Threads
in BASiCS_MCMC
to indicate
default value.
Changes in version 2.1.10 (2020-09-30)
Documents Threads
argument.
Changes in version 2.1.9 (2020-09-28)
Add Threads
argument to BASiCS_MCMC
, allowing parallelisation of
MCMC
updates across cells or genes using openMP.
Reduce BatchInfo requirement for no spikes sampler to a warning, from an error.
Changes in version 2.1.8 (2020-09-28)
Minor edit in the vignette to recommend the use of a seed for
reproducible
results when using BASiCS_MCMC
.
Changes in version 2.1.7 (2020-09-23)
Bugfix in format method for ResultVG class.
For BASiCS_PlotDE
, if only one plot is produced, the plot is
returned as
a bare ggplot object rather than using cowplot::plot_grid
Added EpsilonThreshold
argument for BASiCS_DetectHVG
and
BASiCS_DetectLVG
.
This uses a threshold on epsilon values to identify LVGs and HVGs.
Also adds a MinESS
argument to BASiCS_DetectHVG
and
BASiCS_DetectLVG
.
Deprecated newBASiCS_Data
and the format
methods for Results
classes.
For the latter, use as.data.frame
instead.
Improved documentation for BASiCS_ResultVG class
BASiCS_MCMC
now computes and stores ESS as an attribute of
parameter
matrices when sampling has completed.
Make use of Parameter argument consistent across several methods, where Param and Which were used before.
Extended BASiCS_DiagPlot to enable other diagnostic measures
Moved to store molecule counts in rowData(altExp(sce))
rather than
metadata(sce)
Remove dependency to KernSmooth
Set some values to NA if they relate to genes captured in < 2 cells
Add option to exclude spike-ins in BASiCS_DenoisedCounts
.
Also use a slightly more principled calculation internally.
See issues #182, #39, #91, #169, #181, #178, #202, #190, #173
Changes in version 2.1.6 (2020-08-05)
Prevents usage of BASiCS_VarThresholdSearchVG
when using residual
overdispersion parameters
Changes in version 2.1.5 (2020-08-05)
Minor change on the definition of OrderVariable
within
BASiCS_DetectVG
Changes in version 2.1.4 (2020-08-05)
Extended unit tests to verify the validity of input parameters for
BASiCS_DetectLVG
and BASiCS_DetectHVG
.
Updated documentation for BASiCS_DetectVG
to account for new
default values
and the type of output (now object with class BASiCS_ResultVG
).
Unit tests for LVG updated as new default value for ProbThreshold
is used
whenever the EFDR calibration fails (2/3 as opposed to 0.5).
Minor changes in BASiCS_VarThresholdSearch
to avoid errors in the
presence
or absence of epsilon. This function is likely to be deprecated.
Updates default probability threshold in .ThresholdSearch
when EFDR
calibration fails. This is now set to ProbThreshold
(not 0.9)
Changes in version 2.1.3 (2020-07-29)
New default values for PercentileThreshold
(= NULL), VarThreshold
(= NULL)
and ProbThreshold
(= 2/3) in BASiCS_DetectVG
). The latter is
compatible with
the default values in BASiCS_TestDE
.
Changes default behaviour of BASiCS_DetectLVG
, BASiCS_DetectHVG
in
accordance with the changes introduced for BASiCS_DetectVG
.
Changes in version 2.1.2 (2020-07-29)
Moves auxiliary functions related to HVG/LVG analysis to
utils_VG.R
. This
includes .VGPlot
, .VGGridPlot
, .HeaderDetectHVG_LVG
and .VG
.
Updated warning messages in .HeaderDetectHVG_LVG
Updated rules for EFDR
and ProbThreshold
parameters in
BASiCS_DetectVG
.
If EFDR = NULL
, EFDR calibration is not used and posterior
probability
threshold is set to be equal to ProbThreshold
. This behaviour is
consistent
with the rules used in BASiCS_TestDE
.
Creates .CheckProbEFDR
to perform validity checks for
ProbThreshold
and
EFDR
in all tests (HVG/LVG and DE).
Cleans code within .ThresholdSearch
and BASiCS_DetectVG
Removes Threshold
from the output provided by BASiCS_DetectVG
Removes duplicated plotting code in BASiCS_DetectVG
. Now calls
BASiCS_PlotVG
.
Changes .VGGridPlot
and .VGPlot
to use ggplot2:theme_classic()
Changes in version 2.1.1 (2020-07-28)
Bugfix in BASiCS_DetectHVG and BASiCS_DetectLVG. Epsilon/Delta,Sigma values were erroneously not returned.
More detailed colouring of differential expression plots.
Bugfix in labels for DE plots.
Changes in version 1.2.0
Added support for different Conda channels in the BasiliskEnvironment() constructor.
Added locking to setupBasiliskEnv() for safe parallel construction of environments.
Ensure that environments are always activated before use in useBasiliskEnv().
Changes in version 1.2.0
Migrated most environment-related functions to basilisk.
Added locking to installConda() for safe parallel lazy Conda installations.
Switched to the latest Miniconda3 installer.
Changes in version 1.6.0
Allow regressBatches() to operate without batch= when design= is provided. Added d= and related options to conveniently perform a PCA on the ResidualMatrix.
Added correct.all= option to all correction functions for consistency.
Added a deferred=TRUE default to multiBatchPCA and its callers, to encourage use of deferred matrix multiplication for speed.
Switched default PCA algorithm in multiBatchPCA to IrlbaParam.
Added add.single= mode for endomorphic addition of correction results in correctExperiments().
Changes in version 0.99.8
Minor improvements and fixes
spatialCluster() and spatialEnhance() now use a faster implementation of the multivariate normal density that reduces runtime by approximately 40%.
Changes in version 0.99.7
Minor improvements and fixes
In qTune(), the min_rep and max_rep parameters have been replaced with burn.in and nrep, respectively, to be consistent with spatialCluster().
Changes in version 0.99.6
New features
Minor improvements and fixes
Minor internal refactoring.
Changes in version 0.99.5
Minor improvements and fixes
In spatialCluster() and spatialEnhance(), setting burn.in equal to nrep now raises an error.
Changes in version 0.99.4
New features
Minor improvements and fixes
In featurePlot(), additional arguments to geom_polygon() are correctly passed through.
Changes in version 0.99.3
Minor improvements and fixes
Updated README.md to include system requirements, additional installation details, and link to vignette with demonstration of package functions, per journal guidelines.
Changes in version 0.99.2
Minor improvements and fixes
Figures in the demonstration vignette have been updated with this fix.
Changes in version 0.99.1
Minor improvements and fixes
Removed Maintainer field from DESCRIPTION to adhere to Bioconductor guidelines.
Changes in version 0.99.0
New features
Changes in version 1.5.3
Add function generate_slurm_indexes
generating kallisto
indexes on a cluster with slurm queing system
Add function generate_slurm_calls
generating expression
calls on a cluster with slurm queing system
Update documentation
Add ?BgeeCall documentation with link to main functions
Changes in version 2.14.1
Changes in version 1.5.1 (2020-08-23)
plotClusters() function now has option for superimposing pairs or whole data using the showPairs parameter.
Changes in version 1.25
DEPRECATION ANNOUNCEMENT
NEW FEATURES
(1.25.4) Check for single colon typos when using qualified imports pkg::foo()
(1.25.1) Check for warning/notes on too-brief a Description: field (@federicomarini, #65)
(1.25.8) Validate ORCID IDs (if any) in the DESCRIPTION file (@LiNk-NY, #97)
(1.25.10) Add check for properly formatted CITATION file
(1.25.12) Add NOTE to change dontrun to donttest
BUG FIXES
(1.25.14) The ORCID ID check now accepts IDs with a X at the end.
(1.25.9) All packages including infrastructure require a vignette
Usage of donttest and dontrun in manual pages tagged with the keyword ‘internal’ will no longer trigger a NOTE (@grimbough, #59)
(1.25.7) Adding the sessionInfo at the end of the vignette (@llrs)
USER SIGNIFICANT CHANGES
(1.25.3) Require Aurhors@R format over Author/Maintainer fields in the DESCRIPTION file. This has been upgraded to an ERROR.
(1.25.2) Resolve https://github.com/Bioconductor/BiocCheck/issues/57: Suggest styler over formatR for automatic code re-formatting.
(1.25.5) Add warning to new package versions with non-zero x version (@mtmorgan, #101)
Changes in version 1.24
BUG FIXES
(v.1.23.1) bpvalidate() detects variables defined in parent environments; warns on use of global variables.
(v.1.23.2) bplapply() runs gc() after each evaluation of FUN()
, so
that workers do not accumulate excessive memory allocations (memory
on a per-process basis is not excessive, but cluster-wise could be).
See
https://github.com/Bioconductor/BiocParallel/pull/124:x
Changes in version 1.3
BUG FIX
(1.3.5) Improve GeneSetCollection
functionality.
(1.3.3) Fix failing tests for kegg_set()
.
(1.3.1) Fix failing tests due to new version of GO.db.
NEW FEATURES
(1.3.6) Made the switch from import/export functionality in rtracklayer to BiocIO.
(1.3.4) Extending our export functionality to allow for OBO files. Also create functions to disply relationships of an OBOSet object.
(1.3.2) Extending our import functionality to allow for OBO files.
Changes in version 1.6.0
Changes in version 0.99.0
NEW FEATURES
Changes in version 1.57.0
NEW FEATURES
BUG FIX
(1.57.4) In NEWS generation, fix formatting.
(1.57.1) In VIEWS generation fix but with vignetteTitles. When combinding different format types could potentially remove vignette titles that ended with “RNA,”. Do strict start of and end of string check for formatting.
Changes in version 2.46.0
BUG FIXES
Changes in version 1.5.7
Improved description in the tutorial (BioMM() function returns the prediction scores instead of metrics)
Updated BioMMstage2pred() and BioMM() functions to get prediction scores instead of performance metrics
Updated getMetrics() to cope with the ‘probability’ predicted score as well.
Changes in version 1.5.4
Improved description in the tutorial
Changes in version 1.5.2
updated R functions for reporting results and plotting.
added another omics data (gene expression) and KEGG pathway.
updated tutorial by demonstrating BioMM with another omics data (gene expression) and KEGG pathway annotation.
Changes in version 1.17.2
MINOR MODIFICATION
Changes in version 0.99.0 (2020-02-14)
Changes in version 1.7.2
Added new function to allow for removal of spikes in read coverage present in composite files.
Changes in version 1.7.1
Added new deltaW calculator that allows to define multiplication of the original window size to use for deltaW calculations. One can invoke this by setting ‘multi.sizes’ parameter.
Changes in version 1.1.3
Various minor efficiency & formatting changes
Changes in version 1.1.1
Changes in version 1.99.1
BUG FIXES
no more downloading of databases in the examples
Changes in version 1.99.0
BUG FIXES
Added missing NEWS section for 1.23.1
BridgeDb 3.0.0-SNAPSHOT (2020-10-18)
Changes in version 1.23.1
SIGNIFICANT USER-LEVEL CHANGES
Changes in version 1.31.4
BUG FIXES
Update end coordinates before start coordinates in the function
.aggregateTagClustersGR()
. This should stop triggering
“‘width(x)’ cannot contain negative integers” errors.
Changes in version 1.31.3
BUG FIXES
Correct .make.consensus.clusters
internal function. This should
stop
triggering “Consensus clusters must not overlap with each other”
errors.
Changes in version 1.31.2
BUG FIXES
Allow empty CTSS.chr
objects.
Correct plotInterquantileWidth()
to really use consensus clusters
when passed the argument `clusters = “consensusClusters”.
Fix failures on CAGEexp
objects containing only one sample.
Changes in version 1.45.2
BUG FIXES
Changes in version 2.7.2 (2020-10-21)
SIGNIFICANT USER-VISIBLE CHANGES
For ‘mzAlign()’, the ‘ref’ parameter now expects a vector of reference m/z-values rather than a complete spectrum
Changes in version 2.7.1
BUG FIXES
Fixed issue where ‘spatialDGMM()’ would sometimes fail for features with singular segmentations
Suppressed warnings on ‘Mclust()’ initialization to ‘spatialDGMM()’ caused by R 4.0 changes
Fixed pixel/feature mapping in ‘spatialDGMM()’ metadata
Changes in version 1.12.0 (2020-04-08)
New Features
Terms are updated. Package can recongize even more cancer studies!
Improvements for methylation analysis.
If desired genes are entered as a vector, they are converted to a list without returning an error.
Changes in version 2.2.0
New features
Bug fixes and minor improvements
Changes in version 0.99.0 (2020-09-28)
Submitted to bioconductor.
Changes in version 1.7.1
Compatible with R 4.0.0
Bugfixes:
Changes in version 1.0.2
Changes in version 0.99.1
Documentation improvements.
Changes in version 0.99.0
Changes in version 2.18.2
Changes in version 1.17.1 (2020-09-08)
Changes in version 3.23.12
fix the bug for genomicElementDistribution when the order of SortedByQueryHits is incorrect.
Changes in version 3.23.11
use seqlevelsStyle to reformat the seqlevels for annotation.
Changes in version 3.23.10
update documentation for genomicElementDistribution
Changes in version 3.23.9
add new function enrichmentPlot, genomicElementDistribution, genomicElementUpSetR, and methagenePlot to improve visualization.
Changes in version 3.23.8
update documentation for findOverlapsOfPeaks.
Changes in version 3.23.7
update documentation for findOverlapsOfPeaks.
Changes in version 3.23.6
change parameter from otherCount to otherCounts to makeVennDiagram function.
Changes in version 3.23.5
add plot parameter to makeVennDiagram function.
Changes in version 3.23.4
update README file.
Changes in version 3.23.3
use roxygen2 to generate the help file.
move multiple package from Imports to Suggests.
Changes in version 3.23.2
fix the issue for new paste output.
Changes in version 3.23.1
remove dependence of Rfast
Changes in version 1.25.1
Changes in version 0.99.0 (2020-10-23)
Changes in version 1.14.2
BUG FIXES
Corrected format check for experiment.table: Spaces are not excepted any longer, because they lead to downstream errors.
Changes in version 1.14.1
BUG FIXES
Changes in version 1.17.2
Introduced the use of rJava in getLinearSubpath().
Introduced futures in class LinearPaths.
Changes in version 1.3.1
Added files to fix bugs
Changes in version 1.27.1
Changes in version 1.27.1 (2020-06-05)
Changes in version 3.17.5
update [[.compareClusterResult (2020-10-14, Wed)
Changes in version 3.17.3
read.gmt.wp for parsing gmt file downloaded from wikiPathways
Changes in version 3.17.2
https://github.com/YuLab-SMU/clusterProfiler/pull/290
Changes in version 3.17.1
Changes in version 1.1.2 (2020-09-21)
USCS cell browser reference building
Tutorial update
Bug fixes
Changes in version 1.1.0 (2020-05-21)
Bioc release
Bug fixes
Changes in version 1.21.2
Changes in version 1.5.5
add enforce
argument in get_signatures()
.
subset
can be a vector of indices in
consensus_partition_by_down_sampling()
.
Changes in version 1.5.3
predict_classes()
is speeded up 2x.
get_signatures()
: add top_signatures
argument to control the
number of
top signatures.
Changes in version 1.5.2
add a DownSamplingConsensusPartition
class and corresponding
methods.
add back HierarchicalPartition
class and corresponding methods.
Changes in version 1.5.1
add a predict_classes()
function.
add the cola analysis for Golub dataset as a data object in the package.
automatically install the “suggested” packages.
Changes in version 2.5.6
ht_shiny()
: add argument app
.
grid.dendrogram()
: change the recursive implementation with
iterations.
change default raster device to CairoPNG
.
Heatmap()
: If the discrete col
covers more than the levels in the
matrix,
the full color set is still saved, which means, in
heatmap_legend_param
you
can set at
that are not all in the matrix but are in the col
.
padding of the whole plot and spaces of column titles are adjusted to fit ggplot2
add row_gap
and column_gap
in Legend()
.
oncoPrint()
: now draw legends the same as alter_fun
.
add a new function attach_annotation()
.
legends for row annotations can be grouped with column annotation legends.
annotation name allows rotations.
Changes in version 2.5.5
still draw the legend when all values are NA in an annotation.
add show_fraction
argument in anno_oncoprint_barplot()
function
to show the fractions
of mutations instead of the counts.
pheatmap()
: improve the setting of color
and breaks
.
ht_opt$TITLE_PADDING
can be set with a unit of length two.
HeatmapAnnotation()
: remove colors that are not in the annotations.
pheatmap()
: fixed a bug when length(breaks) = length(color) + 1
pheatmap()
: legend breaks are centered to zero if the matrix is
scaled.
pheatmap()
: color mapping is symmetric to zero when scale is set.
support ragg package to write temporary png files
densityHeatmap()
: column dendrogram is reordered by column means
for ks method.
Changes in version 2.5.4
fixed a bug where slice clusters were wrongly reordered.
Heatmap()
: add border_gp
argument.
Legends are nicely placed.
anno_block()
: allows to set height and width.
support better rasterization.
support setting graphics on dendrogram nodes.
Add a new vignette “interactive heatmap”
Legends()
: fixed a bug of mixtype “legend” to “Legend”.
now assign correct envir to decorate_dend()
.
pheatmap()
: check NA
in the matrix.
grid.dendrogram()
: consider branches with height zero.
checking the dimension of the matrix and the nobs of annotations when adding them.
Changes in version 2.5.3
add selectArea()
/selectPosition()
which allows interactively
select a region from
the heatmaps.
export the heatmap as a shiny app!!!
col
in Heatmap()
accpets a ColorMapping
object.
default_col()
: print a message if there are outliers in the matrix.
discrete_legend_body()
: adjust ncol and nrow if there are empty
rows and columns in the layout.
anno_image()
: fixed a bug that images are not reordered.
anno_mark()
: now expression is correctly supported.
anno_zoom()
: order of index in panel_fun
is adjusted to the order
in the heatmap
list_to_matrix()
: convert elements to characters.
print messages for anno_mark()
, anno_zoom()
, draw_legend()
(if
legends are wrapped)
if working under RStudio.
Changes in version 2.5.2
translate pheatmap to Heatmap
upset_top_annotation()
and upset_right_annotation()
: the names of
the annotations
are changed to intersection_size
, set_size
and union_size
.
list_components()
: adds pattern
argument.
Changes in version 2.5.1
A temporary solution of the sum of two complicated units (in temp.R).
Changes in version 1.1.5
Added vignette documenting LongTable accessors and usage of the new object.
Changes in version 1.0.2
Bug fix: suppress warnings thrown by piano::runGSA inside the connectivitScore function
Changes in version 1.0.1
Changes in version 1.29.2
added parameters such as predIndelFreq to allow the prediction of indels and their frequecies for Cas9 targeted sites
Changes in version 1.29.1
added parameter calculategRNAefficacyForOfftargets, default to TRUE.
Changes in version 1.24.0
Changes in version 1.8
Interactive functions for loading data and analysing results
Major changes
Simplify tutorial
Changes in version 1.6.1
Bug fixes and minor changes
Changes in version 1.1.0 (2020-10-02)
Initial version
Changes in version 0.99.5 (2020-10-09)
Addressed hard links in functions like “processDrugage”
Changes in version 0.99.0 (2020-09-30)
Changes in version 1.1.6 (2020-10-23)
Dropped 32-bit Windows support
Changes in version 1.1.5 (2020-10-11)
Prepared for Bioc 3.12 release
Started unit testing the shiny app
Changes in version 1.1.4 (2020-09-13)
Allow channel-specific inputRange inputs for normalisation
Changes in version 1.1.3 (2020-09-12)
Extended vignette
Changed package title
Changes in version 1.1.2 (2020-07-17)
Added shiny app to package
Changes in version 1.1.1
Images are no longer re-normalized after channel merging (> 3 channels)
Instead images are clipped at 1 leading to brighter colours
The same happens for colour merging when colouring masks by feature expression
Changes in version 3.11
API Changes
Fixes/internal changes
Add CytoML XSD to installation
Changes in version 3.10
API Changes
Change handling of quad gates according to RGLab/cytolib#16
Renaming of methods:
compare.counts -> gs_compare_cytobank_counts
Renaming of classes:
flowJoWorkspace -> flowjo_workspace
Fixes/internal changes
Changes in version 0.99.6 (2020-06-19)
Remove INFO/WARNING/ERROR tags
Add vignettes
Changes in version 0.99.5 (2020-06-18)
Re-build this package
Changes in version 0.99.4 (2020-06-05)
Change examples and provide use case
Changes in version 0.99.3 (2020-06-02)
Update for the comments from the reviewer
Changes in version 0.99.2 (2020-05-24)
Update R version to 4.0
Changes in version 0.99.1 (2020-05-10)
Fixed some warnings in BiocCheck
Changes in version 0.99.0 (2020-05-10)
First commit
Changes in version 1.27.9
update the hyperlink of p.adjust.methods in documentation.
Changes in version 1.27.8
add adjust p-value for testDAU function.
Changes in version 1.27.7
optimize the label position of markers for logo.
Changes in version 1.27.6
add markers for logo.
Changes in version 1.27.5
allow multiple species for prepareProteome.
Changes in version 1.27.3
fix the typo in dagLogo documentation.
Changes in version 1.27.2
add availableSchemes function.
fix the x-axis.
Changes in version 1.27.1
adjust the Depends, Imports and Suggests packages
Changes in version 1.1.3
Add CITATION
Remove “bad chromosome” filtering
Argument build
in extract_bams() removed
Changes in version 1.1.2
Remove vcfR dependency and add VariantAnnotation
Changes in version 1.1.1
Fix typo in split_bams that excluded some chromosomes
Changes in version 0.99.2
NEW FEATURES
Merge documentation into one man page for junction, coverage and outlier processing functions to reduce runtime of roxygen examples.
Changes in version 0.99.1
NEW FEATURES
Change outlier_detect() to using basilisk for interfacing into python replacing reticulate.
Changes in version 0.99.0
NEW FEATURES
Changes in version 2.4.1 (2020-07-27)
Removed dependency of package CRAN vcfR (archived on 2020-07-05), using functions of Bioconductor package VariantAnnotation instead
Improved the mutation filtering so that multiallelic SNVs aren’t excluded when loading tumor genomes from a VCF file
Updated citation and affiliation information
Added consistency check for reference genome and genome annotation
Improved error messages
Changes in version 1.99.3 (2013-07-25)
Updates
A few changes to shearwater vignette
Renamed arguments pi.gene and pi.backgr in makePrior()
Bugfixes
Fixed bug in bf2Vcf() when no variant is called
Changes in version 1.99.2 (2013-07-11)
Updates
Updated CITATION
Added verbose option to bam2R to suppress output
Changed mode() to “integer” for value of loadAllData()
Bugfixes
Fixed bug when only one variant is called in bf2Vcf()
Changes in version 1.99.1 (2013-06-25)
Updates
Using knitr for prettier vignettes
Including shearwater vignette
Bugfixes
fixed issues with deletions in bf2Vcf()
makePrior() adds background on all sites
Changes in version 1.99.0 (2013-04-30)
Updates
New shearwater algorithm
Including VCF output through summary(deepSNV, value=”VCF”)
Changes in version 0.99.13
bug fix and version bump .
Changes in version 0.99.12
version bump.
Changes in version 0.99.11
fix a bug in plot_coverage function and make changes in color scheme.
Changes in version 0.99.10
Made additional required changes from review
Changes in version 0.99.9
Made most required changes from review
Changes in version 0.99.8
SUBMIT TO BIOCONDUCTOR FOR REVIEW
Changes in version 1.25.1
Changes in version 0.16.0
NEW FEATURES
Added ‘as.sparse’ argument to read_block() (see ?read_block) and to AutoRealizationSink() (see ?AutoRealizationSink).
SparseArraySeed objects now can hold dimnames. As a consequence read_block() now also propagates the dimnames to sparse blocks, not just to dense blocks.
Matrix multiplication is now sparse-aware via sparseMatrices.
Added is_sparse<- generic (with methods for HDF5Array/HDF5ArraySeed objects only, see ?HDF5Array in the HDF5Array package).
Added viewportApply() and viewportReduce() to the blockApply() family.
Added set_grid_context() for testing/debugging callback functions passed to blockApply() and family.
SIGNIFICANT USER-VISIBLE CHANGES
Renamed first write_block() argument ‘x’ -> ‘sink’
Renamed: RealizationSink() -> AutoRealizationSink() get/setRealizationBackend() -> get/setAutoRealizationBackend() blockGrid() -> defaultAutoGrid() row/colGrid() -> row/colAutoGrid()
The utility functions for retrieving grid context for the current block/viewport should now be called with no argument (previously one needed to pass the current block to them). These functions are effectiveGrid(), currentBlockId(), and currentViewport().
BUG FIXES
Various fixes and improvements to block processing of sparse logical DelayedMatrix objects (e.g. DelayedMatrix object with a lgCMatrix seed from thr Matrix package).
Fix extract_sparse_array() inefficiency on dgCMatrix and lgCMatrix objects.
Switch matrix multiplication to bplapply2() from bpiterate() to fix error handling.
Changes in version 1.12.0
Dispatch to sparseMatrixStats for sparse seeds that do not have their own methods (<URL: https://github.com/PeteHaitch/DelayedMatrixStats/pull/65>).
Fix center= handling for all affected functions (<URL: https://github.com/PeteHaitch/DelayedMatrixStats/pull/65>).
DelayedMatrixStats now imports the generics from MatrixGenerics. Thanks to Aaron Lun resolving this (<URL: https://github.com/PeteHaitch/DelayedMatrixStats/pull/62>).
Changes in version 1.6.0
MPI for parallel computing is avaliable under R 4.0.0 for linux and Mac OS platforms.
Gene expression data of normal tissues (Lung, Prostate and Thyroid) from the GTEx study are included.
Rename DeMixT_S1 function to DeMixT_DE.
Changes in version 0.99.0 (2020-09-24)
Changes in version 1.5.4 (2020-09-17)
Correction of the information about the content of the output from depeche.
Changes in version 1.5.3 (2020-07-02)
Correcting the p-adjustments, so that it in fact uses Benjamini-Hochberg, and
not the more conservative Hochberg, as default.
Changes in version 1.5.2 (2020-06-05)
Introducing samplingSubset in the depeche function
Bug fixes in dOptPenalty
Small text updates to main vinjette and examples, without code implications.
Changes in version 1.5.1 (2020-05-18)
Introduction of neighSmooth - a generalization of groupStatPlot.
Bug fix and simplification of dOptPenalty termination criteria.
Re-tidying of the code base.
Changes in version 1.30.0
Major overhaul of dispersion estimation and GLM estimation functions from Constantin Ahlmann-Eltze, which will allow use of the glmGamPoi package from within DESeq2, in particular relevant for single-cell datasets. DESeq() can be directed to use glmGamPoi for dispersion and GLM fitting by specifying fitType=”glmGamPoi”. The glmGamPoi estimation is much faster than original DESeq2 estimation for single-cell datasets, e.g. for 30,000 cells, calling glmGamPoi was 13x faster than original DESeq2. In addition, the dispersion estimation is more accurate for genes with many small counts, as found in single-cell datasets. See glmGamPoi manuscript for details on methods, doi: 10.1101/2020.08.13.249623.
Added integrateWithSingleCell(), written by Kwame Forbes, which directs user to a menu of single-cell datasets available on Bioconductor and downloads/loads the one chosen by the user for further analysis visualization. (Interactive only)
Changes in version 1.3.0 (2020-09-30)
Changes in version 1.1.5
ananlyteFDR to limit features for multipeptide.
Removed decoy from features.
BugFix alignment if all intensities are zero.
Fixed printed stats.
Changes in version 3.0
The main upgrade involves how the modelling and normalization are done. DiffBind now supports models and contrasts of arbitrary complexity using either/both DESeq2 or/and edgeR, as well as a myriad of normalization options.
NB:
The previous methods for modelling are maintained for backward compatibility, however they are not the default. To repeat earlier analyses, dba.contrast() must be called explicitly with design=FALSE. See ?DiffBind3 for more information.
The default mode for dba.count() is now to center around summits (resulting in 401bp intervals). To to avoid recentering around summits as was the previous default, set summits=FALSE (or to a more appropriate value).
Normalization options have been moved from dba.analyze() to the new interface function dba.normalize(). Any non-default normalization options must be specified using dba.normalize().
Summary of Changes:
• dba.analyze():
• Automatic mode can start at any point, including from a sample sheet, and continue default analysis
• Remove normalization options bSubControl, bFullLibrarySize, filter, and filterFun from dba.analyze(), now set in dba.normalize().
• Add support to analyze using full model design formula.
• Update DESeq2 analysis method.
• Update edgeR analysis method.
• Moved edgeR bTagwise parameter to $config option
• Remove support for DESeq analysis method.
• Add ability to retrieve DESeq2 or edgeR object
• dba.contrast():
• Add design parameter to set design formula
• Add contrast parameter to specify contrast using variety of methods
• Add reorderMeta parameter to set factor value order
• Add bGetCoefficients parameter to get design coefficient names to use in contrasts
• NEW: dba.normalize():
• Support TMM, RLE, and Library size noramlization for both DESeq2 and edgeR
• Support background bin normalization using csaw
• Support offsets and loess fit normalization
• Support spike-in normalization with combined or separate reference genomes
• Support parallel factor normalization
• bSubControl default depend on presence of Greylist
• dba.count():
• Change default to summits=250; to avoid recentering around summits,must set summits=FALSE
• Default for bUseSummarizeOverlaps in dba.count is now TRUE
• Automatically detect single-end/paired-end in dba.count
• Automatically index unindexed bams in dba.count and dba.normalize
• move bSubControl parameter
• Default score is now new score DBA_SCORE_NORMALIZED
• Add minCount parameter to dba.count(), default now 0 instead of 1
• Filtering peak by read count thresholds only available in dba.count()
• Fix bug in dba.count() with user-supplied peakset and summits=n
• NEW: dba.blacklist():
• Apply ENCODE blacklist
• Automatically detect reference genome for blacklist
• Apply Greylists
• Generate Greylists from controls using GreyListChIP package
• Plotting changes:
• Add loess fit line to dba.plotMA()
• Add ability in dba.plotMA() to plot aribitrary samples (without contrast).
• Add mask parameter to dba.plotBox()
• Support negative scores, eg Fold changes in report-based objects, to enable fold-change heatmaps.
• Removed bCorPlot as a parameter to dba(), dba.count(), and dba.analyze(). Use config.
• dba.show() / print changes:
• Updated dba.show() and print() to deal with designs and different contrast types
• Add ability to retrieve design formula in dba.show()
• Removed bUsePval parameter in dba.show()
• Added constant variable DBA_READS to access library sizes
• Vignette and help pages:
• Replace multi-factor analysis section
• Add extensive normalization section
• Add blacklist/greylist section.
• Add pike-in and parallel normalization examples
• Add DiffBind3 help page and vignette section with information on backward compatibility.
• Update technical details sections
• General updates to all sections
• Add GenerateDataFiles.R to package
• Various bugfixes and cosmetic changes.
Changes in version 1.15.1 (2020-10-04)
Changes in version 1.5.6 (2020-07-22)
Visual change to screen plot (No longer apply alpha to “after”).
Bug fixes.
Changes in version 1.0.3
FC and log2-FC calculation added (via ‘log2_FC’ function);
‘top_results’ function edited to sort results by p-value and log2-FC.
Changes in version 1.0.1
substantial speed-up in distinct_test
(~7 times faster);
parallel computing introduced;
modelling of covariates introduced, via a design matrix;
two new functions to visualize results: plot_cdfs
and
plot_densities
.
Changes in version 1.2
Added 3 New Visualization Functions, dittoDotPlot()
,
dittoDimHex()
& dittoScatterHex()
.
Expanded SummarizedExperiment compatibility across the entire toolset.
Added ComplexHeatmap integration to dittoHeatmap()
,
controlled by a new input, complex
.
Added Rasterization for improved image editor compatibility of complex plots. (See the dedicated section in the vignette for details.)
Added labels.split.by
input & do.contour
, contour.color
,
and contour.linetype
inputs to scatter/dim-plots.
Added order
input to scatter/dim-plots for control of
plotting order.
Added metas
input for displaying such data with
dittoHeatmap()
.
Added adjustment
input to meta()
, which works exactly as in
gene()
(but this is not yet implemented within data grab of
visualiation functions).
Added adj.fxn
input to meta()
aand gene()
for added
control of how data might be adjusted (but this is not yet
implemented within data grab of visualiation functions).
Replaced (deprecated) highlight.genes
input with
highlight.features
in dittoHeatmap()
.
Replaced (deprecated) OUT.List
input with list.out
for all
multi_*
plotters.
Changes in version 1.3.1
New Features
Removed
Changes in version 1.11.1
CHANGES
BUG FIX
Changes in version 3.15.4
update setReadable and geneInCategory methods for compareClusterResult object (2020-10-12, Mon)
Changes in version 3.15.3
https://github.com/YuLab-SMU/DOSE/pull/39
Changes in version 3.15.2
Changes in version 1.9.0
Changes in version 1.10.0
Migrated downsampleMatrix() to scuttle with a re-export.
Added features= to downsampleReads() for per-feature-set downsampling.
Added matrix support for y= and ambient= in maximumAmbience().
Added controlAmbience() for easy estimation of ambient contamination with control features.
Added removeAmbience() function to remove the ambient solution from a count matrix, mostly for aesthetics.
Report library index and feature type in output of read10xMolInfo().
Support subsetting by library index/type in functions that use the molecule information file, such as swappedDrops() and chimericDrops().
Added by.rank= option to estimateAmbience() and emptyDrops(), for estimation of the ambient profile by excluding barcodes with the largest totals.
Added exclude.from= option to barcodeRanks(), to avoid problems with instability at low ranks for knee/inflection calculations (contributed by Stefano Mangiola).
Minor bugfix in barcodeRanks() calculation of the knee point. Note that this affects the default choice of retain= in emptyDrops().
Split off HTO ambience inferences into a separate inferAmbience() function.
Added support for combinatorial barcodes in hashedDrops().
Changes in version 2.25.1
Ported changes from 2.24.1
Changes in version 2.24.1
Final documentation fix and removal of defunct RangedData unit tests.
Changes in version 2.23.1
Removed coercion methods to CountDataSet
following DESeq
deprecation.
Updated vignette to show how to use EDASeq
with DESeq2
.
Changes in version 3.32.0
cpm.default() and rpkm.default() now accept offset.
scaleOffset() now accepts CompressedMatrix offset and accounts for norm.factors.
Revise the lowess trend fitting in voomLmFit() to downweight genes with exact zeros and hence fewer df to estimate the variance.
Add as.data.frame method for DGEList class.
Change default choice for refColumn in calcNormFactors() with method=”TMMwsp”. The new method chooses the column with the largest sum of sqrt-counts.
processAmplicons() can now accommodate data from newer screens that use a staggered primer design.
Fixed a bug that diffSpliceDGE() accept more than one coef. It now gives a warning if more than one coef or contrast is supplied. It only uses the first.
Changes in version 3.30.2
New function voomLmFit() that combines the limma voom-lmFit pipeline with loss of residual df due to zero counts as for glmQLFit(). The new function is more robust to zero counts than running voom() and lmFit() separately. The new function allows sample quality weights and intra-block correlations to be estimated it incorporates the functionality of duplicateCorrelation() and voomWithQualityWeights() as well.
New function SE2DGEList() to convert a SummarizedExperiment object into a DGEList object.
S3 methods for SummarizedExperiment objects are added to the following functions: aveLogCPM(), calcNormFactors(), cpm(), cpmByGroup(), estimateDisp(), filterByExpr(), glmFit(), glmQLFit(), plotMD(), plotMDS(), predFC(), rowsum(), rpkm(), rpkmByGroup() and sumTechReps().
New cpm and rpkm methods for DGEGLM and DGELRT objects.
New function effectiveLibSizes() to extract normalized library sizes from an edgeR data object or fitted model object.
Add as.data.frame methods for DGEExact and DGELRT objects and remove the ‘optional’ argument from as.data.frame.TopTags().
readBismark2DGE() now forces ‘files’ to be character vector.
Add warning messages when filterByExpr() is used without specifying group or design.
Add warning message when calcNormFactors() is applied to DGEList object containing an offset matrix.
Rewrite User’s Guide Section 3.5 on Multilevel Experiments so that the code is valid regardless of the number of subjects in each disease group.
Changes in version 1.8
added functionality to encircle variables of interest
added option to remove arrowheads on connectors
added option to rasterise images via ggrastr::geom_point_rast (Benjamin Ostendorf)
changed axis.text.y = element_text(…, vjust = 1.0) to 0.5 (Benjamin Ostendorf)
Changes in version 1.25.9
Changes in version 2.20.0
New function import
to import results from differential expression
analysis with limma, edgeR, and DESeq2
New function showAvailableSpecies
to list supported species
for a gene set database of choice (GO, KEGG, MSigDB, Enrichr, …)
New function showAvailableCollections
to list provided
gene set collections for a supported species of a gene set database
of
choice (GO, KEGG, MSigDB, Enrichr, …)
Gene sets: obtaining and caching of gene sets for different gene ID
types (new argument gene.id.types
for function getGenesets
)
GO gene sets: filter by GO evidence codes (new argument evid
for
function getGenesets
)
Including NEAT among nbea methods
Changes in version 1.9.5
Remove similarity calculation from emapplot
Changes in version 1.9.4
https://github.com/YuLab-SMU/enrichplot/pull/62
Changes in version 1.9.3
add node_label_size parameter to adjust the size of node label in emapplot function (2020-09-18, Fri)
Changes in version 1.9.2
Changes in version 1.32.0
Changes in version 999.999
Changes in version 0.99.9
Changing Seurat dependency, updated vignette
Changes in version 0.99.8
Edited getSignificance ANOVA model call
Changes in version 0.99.7
Edited getSignificance fit call to match documentation
Changes in version 0.99.6
Edited match.args() in getSignificance
Changes in version 0.99.5
Edited match.args() in getSignificance
Changes in version 0.99.4
Added match.args() to getSignificance
Changed stop() to message()
Modified getSignficance to allow for ANOVA and T.test
Changes in version 0.99.3
Updated link in description of getGeneSets.
Changes in version 0.99.2
*Fixed a parenthesis, yeah a parenthesis. (In enrichIt() call I edited for 99.1)
Changes in version 0.99.1
Removed parallel call in gsva() and added biocparallel
Changed cores = 4 to cores = 2 in the vignette
Changes in version 0.99.0
Preparing for bioconductor submission
Changes in version 1.15.0
BUG FIXES
USER-VISIBLE CHANGES
(1.15.4) less stringent internet check
(1.15.3) Add link for github issue reporting
(1.15.1) Add hubs@bioconductor.org email for help
Changes in version 0.99.0 (2020-10-02)
PRE-RELEASE
Changes in version 1.1.4
Changes in version 1.17.1
Changes in version 0.99.9 (2020-10-26)
Updated examples data
Changes in version 0.99.8 (2020-10-24)
Fixed unit tests
Changes in version 0.99.7 (2020-10-19)
Removed UniprotR package
Changes in version 0.99.6 (2020-10-19)
Updated Biocmanager, devel version
Changes in version 0.99.5 (2020-10-19)
Fixed unit tests
Changes in version 0.99.4 (2020-10-16)
Removed biomart package
Changes in version 0.99.3 (2020-10-16)
Updated NEWS file
Changes in version 0.99.2 (2020-10-16)
Updated DESCRIPTION file
Changes in version 0.99.1 (2020-10-01)
Fixed testthat issues
Changes in version 0.99.0 (2020-09-24)
Updated version for Bioconductor submission
Changes in version 0.0.0.9000 (2020-09-01)
Changes in version 3.23
Changes in version 1.15.2
Faster perturbate thanks to Nikolay Budin
Cleaner P-value and error estimations
Changes in version 0.99.3 (2020-10-08)
Fix error in the algorithm under multiple threading
Speed up the filtering process using minMapBase
Changes in version 0.99.0 (2020-08-20)
Submitted to Bioconductor
Changes in version 1.6.0
Added makeInfReps() to create pseudo-inferential replicates via negative binomial simulation from mean and variance matrices. Note: the mean and the variance provide the inferential distribution per element of the count matrix. See preprint for details, doi: 10.1101/2020.07.06.189639.
Added splitSwish() and addStatsFromCSV(), which can be used
to distribute running of Swish across a number of jobs
managed by Snakemake
. See vignette for description of
a suggested workflow. For a large single-cell dataset
with mean and variance summaries of inferential uncertainty,
splitSwish() avoids generating the inferential replicate
counts until the data has been split into smaller pieces and
sent to different jobs, then only the necessary summary
statistics are gathered and q-values computed by
addStatsFromCSV().
plotInfReps() gains many new features to facilitate plotting of
inferential count distributions for single cells, as quantified
with alevin and imported with tximport. E.g. allow for numeric
x
argument plus grouping with cov
for showing
counts over pseudotime across groups of cells. Also added
applySF
argument which can be used to divide out a
size factor, and the reorder
argument which will re-order
the samples/cells within groups by the count. plotInfReps()
will draw boxplots with progressively thinner visual features
as the number of cells grows to make the plots still legible.
Changes in version 1.5.2
First version of makeInfReps(), to create pseudo-infReps via negative binomial simulation from set of mean and variance matrices in the assays of the SummarizedExperiment.
Changes in version 1.0.0
NEW FEATURES
BUG FIXES
Changes in version 1.47.0
The update to R4.0.2 caused warnings like: Warning messages: 1: In .Call(“bin_level”, fcs@exprs, model@.tmp_tags, model@split_axis[[level]], : converting NULL pointer to R NULL. The c code was updated to avoid returning a null pointer.
Updated citation syntax was incorporated in the CITATION file.
Changes in version 1.3.3 (2020-09-03)
Changes to two tests due to minor errors
Excluding the recommendation to use flowVS, due to its deprecation.
Changes in version 1.3.2 (2020-05-15)
Addition of peakNorm and associated test.
Changes in version 1.3.1 (2020-05-15)
Bug fix in arcTrans.
Correcting the way specUnmix exchanges exprs objects.
Changes in version 0.99.3
IMPROVEMENTS SINCE LAST RELEASE
Compatibility with bioconductor is added.
Changes in version 0.99.0
Package moved to bioconductor.
BUG FIXES
Changes in version 1.1.6
Use proper S3/S4 methods to share functions between packages
Minor API changes due to S3/S4 changes (e.g fds -> object)
Switch from psiSite to theta
Improved documentation
Minor bugfixes
Changes in version 1.1.3
Update and adjust injectOutlier and hyperParameter functions
Option to compute z scores in logit space or not
Add cap value [0.01,0.99] to logit function
Use pairedEnd counting with Rsubread
Correct assayName pajd -> padj
Minor bugfixes
Changes in version 1.1.2
Option to consider only the standard chromosomes in the counting
Option to include additional columns from mcols(fds) in the result table
Annotation of junctions with corresponding gene names/ids now produces an additional column in mcols(fds) that contains further gene names/ids if the junction overlaps with multiple genes
Minor bugfixes
Changes in version 1.1.1
Bugfix correcting the strand specific counting for paired-end reads
Changes in version 0.99.7 (2020-09-08)
ReSubmitted to Bioconductor
Changes in version 0.99.6 (2020-08-27)
ReSubmitted to Bioconductor
Changes in version 0.99.5 (2020-08-27)
ReSubmitted to Bioconductor
Changes in version 0.99.4 (2020-08-27)
ReSubmitted to Bioconductor o Remove duplicates of detected PRF events from output
Changes in version 0.99.3 (2020-08-26)
Submitted to Bioconductor
Changes in version 2.39.3
fixed warning on “library(GO.db)” in go.gsets.R. Now “import” from GO.db, instead of “suggest” it.
Changes in version 2.39.2
fixed error caused by class(exprs) == “data.frame” in gagePrep.R. class(exprs) now returns a vector of length 2, which caused the error.
Changes in version 1.5.1 (2020-07-01)
Changed
Changes in version 1.1.6
add gcs_rm function
Changes in version 1.1.5
Add gcloud into the default authentication process
Changes in version 1.1.4
gcs_is_requester_pays supports uri
Better print format in gcs_get_cloud_auth
Changes in version 1.1.3
FileClass object can show the file URL now
no warning will be given if gcs_dir
find a non-standard file path
Fix some word issues: all xxx_url functions are renamed to xxx_uri
Changes in version 1.1.2
Support Requester Pays
Support ~
symbol to go to the bucket root
Support conversion from Folder/File class to character
Changes in version 1.24.1
UTILITIES
print.gds.class()
for array preview Changes in version 2.19.7
Change default value of small.samp.correct in pcrelate to TRUE.
Add options to remove NxN matrices from a null model (function nullModelSmall and fitNullModel argument return.small).
Add check for collinearity in covariates.
Changes in version 2.19.6
Add test options “BinomiRare” and “CMP” to assocTestSingle and assocTestAggregate.
Changes in version 2.19.5
Add function jointScoreTest to perform a joint score test of a set of variants using a null model and a matrix of genotype dosages.
Changes in version 2.19.4
Add function effectAllele to return the effect allele for association tests.
Changes in version 2.19.1
Force design matrices to be non-sparse.
Changes in version 1.2.0
New features
The geneset distillery is officially open! GeneTonic offers functionality to aggregate together gene sets into overarching biological themes, based on a network-based refinement of the enrichment map. Corresponding graphical functionalities are also extended to accommodate meta-genesets. An efficient implementation for the Markov clustering on graph objects is also provided
GeneTonic can now receive the input of many other tools for functional enrichment analysis - this includes the output (text export) of DAVID (shake_davidResult), enrichr (from website and via the package, with shake_enrichrResult), fgsea (shake_fgseaResult), and g:Profiler (with shake_gprofilerResult, which can handle the textual output from the website, as well the one from the call to the gost in gprofiler2)
An export button to a SummarizedExperiment object for iSEE and its underlying machinery has been added. If the visualization options in GeneTonic are not exactly what you would expect, you might find an excellent venue in the iSEE framework
Other notes
Changes in version 1.26.0
NEW FEATURES
The seqlevelsStyle() getter and setter now support style “RefSeq” when the underlying genome is known.
Register a bunch of new NCBI assemblies and UCSC genomes. Use registered_NCBI_assemblies() and registered_UCSC_genomes() to get the lists of supported NCBI assemblies and UCSC genomes.
SIGNIFICANT USER-VISIBLE CHANGES
DEPRECATED AND DEFUNCT
BUG FIXES
Changes in version 1.45.2
Ported changes from 1.44.2
Changes in version 1.45.1
Ported changes from 1.44.1
Changes in version 1.44.2
Updated the maintainer email address
Cleared the imports
Changes in version 1.44.1
Updated the vignette (data.frame() default is not a factor anymore for character vectors in R4)
Removed the defunct RangedData usage
Changes in version 1.42.0
NEW FEATURES
SIGNIFICANT USER-VISIBLE CHANGES
Changes in version 1.3.1
Fixed a bug of always using Enssembl US server to annotate the genes.
Updated the description in the DESCRIPTION file.
Updated the citations.
Changes in version 1.42.0
NEW FEATURES
Add nearestKNeighbors() method for GenomicRanges derivatives.
coverage() now supports ‘method=”naive”’. This is in addition to the already supported methods “sort” and “hash”. This new method is a slower version of the “hash” method that has the advantage of avoiding floating point artefacts in the no-coverage regions of the numeric-Rle object returned by coverage() when the weights are supplied as a numeric vector of type ‘double’. See “FLOATING POINT ARITHMETIC CAN BRING A SURPRISE” example in ‘?coverage’ in the IRanges package.
Changes in version 0.99.16
Functions getDee2Metadata
and queryDee2
are now called
getDee2Metadata
and queryDEE2
respectively to be consistent
with the other functions.
Fixed a bug with some samples that have a # in the name. Thanks to @uilnauyis for the suggestion.
New function getDEE2_bundle to fetch entire project data from http://dee2.io/huge/
Changes in version 0.99.9
New function se() which constructs SummarizedExperiment object
Changes in version 0.0.2
Some slight change to the vignette
Changes in version 2.3.7
add family parameter to geom_tiplab()
Changes in version 2.3.6
https://github.com/YuLab-SMU/ggtree/pull/342
Changes in version 2.3.5
update geom_hilight to support geom_hilight(data = tbl_tree, node = selected_node). (2020-09-03, Thu)
Changes in version 2.3.4
hexpand to expand x limits by ratio of x range and supports both direction (1 for rhs and -1 for lhs) (2020-07-27, Mon)
Changes in version 2.3.3
layout_inward_circular for layout_circular() + scale_x_reverse() (2020-07-16, Thu)
Changes in version 2.3.2
update geom_taxalink to support circular layout tree (2020-07-13, Mon).
Changes in version 2.3.1
Changes in version 0.99.0
the 0.99.0 or 0.99.x version mean I am submitting it to Bioconductor. (20200710, Fri)
0.99.9
0.99.10
0.99.11
0.99.12
0.99.13
0.99.14
0.99.15
0.99.16
0.99.17
0.99.18
0.99.19
modified the namespace, remove geom_vline, add geom_segment. (2020-09-11, Fri)
Changes in version 0.0.1
add vignettes. (20200707, Tue)
Changes in version 0.0.0.9
fixed bug: changed layer to layers. (20200703, Fri)
Changes in version 0.0.0.8
support data of NULL in geom_fruit, and user can add data by %<+% of ggtree. (20200628, Sun)
Changes in version 0.0.0.7
add geom_fruit_list to support add the same position for multi layers. (20200622, Mon)
Changes in version 0.0.0.6
automatically detect the ‘position’. (20200612)
Changes in version 0.0.0.5
change geom_add function to geom_totree function. (20200610)
Changes in version 0.0.0.4
support geom_boxplot and geom_violin (20200606)
Changes in version 0.0.0.3
add marginal line, and when x is character, the new x normalized should be started with zero. (20200601)
Changes in version 0.0.0.2
The distance between the panel and tree can be adjusted using the “offset”. The value of associate panel were normalized in the range of x of tree. The width can be adjusted using the “pratio”. The “offset” and “pratio” are the ratio related to tree. (20200529)
Changes in version 0.0.0.1
Changes in version 2.0.0
Brand new backend and API with major changes
Plots can now be embedded in html reports
Plots can now be saved
Data from gene annotation and counts can now be saved
Added many plot customisation options in MDS plot
Changes in version 1.1
Remove dual likelihood functions for overdispersion estimation. Instead merge functionality into conventional_***. This should cause no user facing changes, however should make it easier to maintain the package
Make conventional_score_function_fast() more robust to extreme inputs. Avoid numerically imprecise subtractions and employ bounds based on series expansions for very small input
If dispersion estimate quits because there is no maximum or all y are 0, return iterations = 0
Add limits (1e-16 / 1e16) for nlminb estimates of the dispersion. This protects against errors due to NA’s in the conventional_likelihood_fast
Automatically set ‘size_factors = FALSE’ for input with 0 or 1 row. This will change the estimated beta, but not the mu’s
Rename gampoi_overdispersion_mle() -> overdispersion_mle()
Store data in the object returned by glm_gp()
Remove Y from the interface of residuals.glmGamPoi, because I can just get it directly from fit$data
Add function test_de() that does a quasi-likelihood ratio test to detect differentially expressed genes
Add functionality to make a pseudobulk test directly from test_de() by aggregating the data around one column
In group-wise beta estimation, fall back to optimize() if the Newton method fails
Change the default size factor estimation method from “poscounts” to “normed_sum” and provide an easy way to call scran::calculateSumFactors()
New “global” mode for dispersion estimation
Changes in version 1.5.5
Add function for similarity scores between given labels for samples and the clustering in each predicted module.
Changes in version 1.5.2
extract_edges() now returns an adjacency matrix for interations and their scores.
Changes in version 2.15.2
update data/gotbl
Changes in version 2.15.1
Changes in version 1.1.0
Made the following significant changes
Incorporate ShinyGPA developed by Emma Kortemeier as a part of the R package.
Add fitAll() to fit GPA models for possible pairs of phenotypes.
Add shinyGPA() to open the shiny app for the interactive pleiotropy visualization.
Changes in version 1.35.2 (2020-10-12)
Changes in version 1.22.0
Add black lists for C. Elegans ce11, mouse dm6.
Update existing black lists to version 2, or version 3 for human GRCh37, GRCh38.
Changes in version 0.99.0
Changes in version 0.99.3 (2020-10-23)
fix several issues acording to bioc revision
add accessor functions to galgo.Obj object
Changes in version 0.99.0 (2020-09-01)
Remove gpuR support
fix problem with small population
Bioconductor Submission
Changes in version 0.5.0 (2020-08-02)
Rename to GSGalgoR
Changes in version 0.4.2 (2020-07-21)
Pre-release before Bioconductor submission
Changes in version 1.33.1
NEW FEATURES
BUG FIXES
Changes in version 2.21.7
USER VISIBLE CHANGES
Oct 19 2020 – peculiar content in CHR_ID and CHR_POS cause truncation. Improved read_tsv call by setting col_types
Changes in version 2.21
USER VISIBLE CHANGES
April 30 2020 – use BiocFileCache to manage retrieval from EBI
May 2 2020 – ebicat_2020_04_30 is a sample of 50000 records from a full retrieval
May 2 2020 – many data() elements moved to inst/legacy, LazyData turned off
Changes in version 1.35.2
Changes in version 1.0.0
New features
Bug fixes and minor improvements
Changes in version 1.18.0
NEW FEATURES
Add ‘as.sparse’ argument to h5mread(), HDF5Array(), HDF5ArraySeed(), writeHDF5Array(), saveHDF5SummarizedExperiment(), and HDF5RealizationSink(). Even though it won’t change how the data is stored in the HDF5 file (data will still be stored the usual dense way), the ‘as.sparse’ argument allows the user to control whether the HDF5 dataset should be considered sparse (and treated as such) or not. More precisely, when HDF5Array() is called with ‘as.sparse=TRUE’, the returned object will be considered sparse i.e. blocks in the object will be loaded as sparse objects during block processing. This should lead to less memory usage and hopefully overall better performance.
Add is_sparse() setter for HDF5Array and HDF5ArraySeed objects.
SIGNIFICANT USER-VISIBLE CHANGES
BUG FIXES
Fix handling of logical NAs in h5mread().
Fix bug in saveHDF5SummarizedExperiment() when ‘chunkdim’ is specified.
Changes in version 0.99.2 (2020-10-19)
Updates for Bioconductor review
Changes in version 0.99.0 (2020-09-17)
Submitted to Bioconductor
Changes in version 1.26.0
users can interrupt the model building in an interactive R session
remove hlaErrMsg()
since it is never used
a new option ‘nthread’ in hlaAttrBagging()
as a complement to
hlaParallelAttrBagging()
kernel version 1.5: generates the same training model as v1.4, but 2-6x faster, by taking advantage of Intel AVX, AVX2 and AVX512 intrinsics
new function hlaSetKernelTarget()
to automatically select the CPU
target the algorithm is optimized for
Changes in version 1.11.1 (2020-08-14)
Add CITATION, also to README.md file
Update NEWS
Update DESCRIPTION o Add Mikhail Dozmorov as Maintainer o Add URL and BugReports fields
Revert breaking changes o KRnormalization.R, line 75, Z = rk/v; rho_km1 = t(rk) %*% Z; o hic_compare.R, line 99, A.min <- ceiling(mean(A_q10))
Changes in version 1.11.0 (2020-02-11)
New method to read in .cool files, cooler2bedpe()
New method for comparison, hic_compare()
Changes in version 0.99.2 (2020-09-02)
R code
Changed high stringency to include Enhanced and Supported removing Approved
Changes in version 0.99.1 (2020-08-06)
Responded to comments from Bioconductor reviewer
DESCRIPTION
Moved tibble
and shiny
to imports
Vignettes
Made installation section
Added table of contents
Updated vignette text to agree with code
Included sessionInfo()
R code
Updated HPA_data_downloader
to fit bioconductor standards
for accesing a website.
Reduced number of lines >80
Reduced number of indents not multiples of 4 spaces
Changes in version 0.99.0 (2020-07-15)
Package prepared for submission to Bioconductor
Updated to coding practices
No Biocheck Errors
Updated imports and examples
Changes in version 1.05.03
rctbl_build() nested tables shows the number of enriched genesets
Changes in version 1.05.02
Relative paths are now supported by hyp_to_rmd()
Changes in version 1.05.01
Added the first shiny module for geneset selection
Changes in version 1.05.00
Changes in version 1.14.0
Other notes
Changes in version 1.2.2
Changes in version 1.3.3 (2020-10-15)
Changes in version 0.31.1 (2020-07-15)
UPDATES
Error messages produced by readIDAT() when failing decrypt no longer appends an extra newline at the end.
readIDAT() uses explicit stringsAsFactors=FALSE internally.
readIDAT() no longer keeps two file connections open at the same.
DOCUMENTATION
BUG FIXES
readBGX() would leave an open connection if there was an file reading error.
Changes in version 0.31.0 (2020-04-27)
NOTES
Changes in version 0.99.0 (2020-06-25)
Changes in version 1.21.2
code cleaning
Changes in version 1.21.1
Changes in version 1.5.3 (2020-10-23)
Add check that detectCores() doesn’t return NA before comparing. In case it does, just use the value provided as an option directly.
Changes in version 1.5.2 (2020-10-23)
Added reordering of cells in metadata exported to a seurat object so that it always matches, in case the cells are not sorted in the same order in the data provided to infercnv and in seurat.
Changes in version 1.5.1 (2020-10-06)
Fix to reload in cases where comparing NULL/NA.
Fixed issue in denoising when trying to reload results from step 18 or 19.
Fixed MCMC Diagnostic plots by adding diagnostic generation.
Update included data objects to contain additional option slot, and prevent common name collisions.
Fully rename data objects and name of the vars they provide.
Fix reference plotting not having access to the actual subclustering information but that of the previous provided data object (that was renamed to avoid name collision by mistake like this one).
Added checks in add_to_seurat methods that there are gains/losses found when taking the top hits.
Added check that output to write in add_to_seurat top regions is not null and output an empty file without erroring if it is.
Change to remove genes in “chr_exclude” from counts before doing the read level filtering of cells.
Added minimum read count requirement per cell of 1 after removal of “chr_exclude” genes so that there are no divisions by 0 when normalizing.
Changed default min_max_counts_per_cell to select cells with at least 100 counts by default.
Fix to plotting for HMM coloring of heatmap when the full range of values are not present.
Fix to plotting when no reference groups are used to not produce warnings.
Changes in version 0.99.8 (2020-10-06)
make changes
Changes in version 0.99.7 (2020-10-06)
make changes
Changes in version 0.99.6 (2020-09-21)
make changes
Changes in version 0.99.5 (2020-09-20)
Fix the the issue reported in the build report where used “1:lenght”” instead of “seq_len”
Use “<-“ for assignment rather than “=”
Fix indentation
Changes in version 0.99.4 (2020-08-14)
Fix the warning of unnecessary package calls
Changes in version 0.99.3 (2020-08-14)
Fix the warning of unnecessary package calls
Changes in version 0.99.2 (2020-08-14)
Fix the warning of unnecessary package calls
Changes in version 0.99.1 (2020-08-13)
Made the following significant changes
Added Informeasure.Rproj into the .gitignore file
Replaced Author/Maintainer with Authors@R in the DESCRIPTION file
Added a NEWS file
Added a .R file in tests/ directory
Update R version dependency from 3.5.0 to 4.0
Use TRUE/FALSE instead of T/F in PMI.plugin()
Changes in version 0.99.0 (2020-08-09)
Submitted to Bioconductor
Changes in version 1.29.0
Notes
Changes in version 2.24.0
NEW FEATURES
DEPRECATED AND DEFUNCT
BUG FIXES
Changes in version 0.99.15 (2020-10-22)
Minor fix in import_association_file file function: added multiple strings to be translated as NA
Changes in version 0.99.14 (2020-10-21)
Minor fixes in tests
Changes in version 0.99.13 (2020-10-19)
NEW FEATURES
Added plotting functions CIS_volcano_plot
Changes in version 0.99.12 (2020-10-04)
NEW FEATURES
SIGNIFICANT USER-VISIBLE CHANGES
MINOR CHANGES
import_parallel_Vispa2Matrices_interactive and import_parallel_Vispa2Matrices_auto now have an option to return a multi-quantification matrix directly after import instead of a list
Changes in version 0.99.11 (2020-09-21)
NEW FEATURES
MINOR FIXES
Fixed issues in some documentation pages
Changes in version 0.99.10 (2020-09-14)
ISanalytics is officially on bioconductor!
NEW FEATURES
SIGNIFICANT USER-VISIBLE CHANGES
MINOR FIXES
Added fix for import_single_Vispa2Matrix to remove non significant 0 values
Changes in version 0.99.9 (2020-09-01)
NEW FEATURES
SIGNIFICANT USER-VISIBLE CHANGES
Modified package documentation
Changes in version 0.99.8 (2020-08-12)
Changes in version 2.1.27
Minor edits to the API documentation.
Changes in version 2.1.26
Separate the maximum number of factor levels for colors from other applications.
Changes in version 2.1.25
Support a named vector in the SearchColumns field of the Table subclasses.
Changes in version 2.1.24
Switch colormap getters to use an internal cache to avoid conflicts with user entries.
Changes in version 2.1.23
ExperimentColorMap inherits from Annotated.
Changes in version 2.1.22
Split and rename scripts for test setup.
Changes in version 2.1.21
Minor fix to unit test.
Changes in version 2.1.20
Minor fixes to the ComplexHeatmapPlot documentation.
Changes in version 2.1.19
Fixes to the underlying reactive framework to avoid bugs due to unresponsiveness.
Changes in version 2.1.18
Bugfix to properly support dynamic classes on landing page.
Changes in version 2.1.17
CSS classes for each panel are now defined at app run-time, to make it easier to write landing pages without specifying initial= in iSEE().
Changes in version 2.1.16
Bugfix for initialization of the ColorByFeatureDynamicSource UI element in ColumnDotPlots.
Changes in version 2.1.15
Turned on validity checks during [[<- assignment into Panel classes.
Changes in version 2.1.14
Allowed custom annotation about selected table row to to be displayed in Table panels.
Changes in version 2.1.13
Refactored the heatmap feature selection modal to be reusable for selecting rows or columns in other contexts.
Changes in version 2.1.12
Generalized the HiddenColumns mechanism to all Table subclasses.
Changes in version 2.1.11
Added HiddenColumns slot to hide columns in ColumnDataTables and RowDataTables.
Changes in version 2.1.10
Streamlined the .defineOutput signature.
Changes in version 2.1.9
Extract assays with dimnames for correct indexing.
Changes in version 2.1.8
Extended control of legend point size for violin plots and Hinton plots.
Changes in version 2.1.7
Added control of legend point size under the “Text” category of teh “Visual parameters” box.
Changes in version 2.1.6
Fixed bug for sizeBy observers.
Changes in version 2.1.5
Fixed removal of last panel from the interface.
Changes in version 2.1.4
Fixed missing section in createLandingPage() man page.
Changes in version 2.1.3
Fixed handling of logical > 1 when processing the CustomRowsText slot in the ComplexHeatmapPlot constructor.
Changes in version 2.1.2
Removed deprecated functionality.
Changes in version 2.1.1
Changes in version 1.1.9
Ensure that global parameters only affect panels during construction.
Changes in version 1.1.8
Added the AggregatedDotPlot panel to show marker-based dot plots.
Changes in version 1.1.7
Improved safety and correctness of the calculation of the number of DEGs.
Changes in version 1.1.6
Version bump to trigger reinstallation with new iSEE class definitions.
Changes in version 1.1.5
Added panel-specific tours for all panel classes via the .definePanelTour() generic.
Changes in version 1.1.4
Align DynamicMarkerTable’s treatment of getTableExtraFields() with the globals strategy.
Changes in version 1.1.3
Switched to KEGGREST to get the names of pathways.
Changes in version 1.1.2
Global parameters now only affect construction of MAPlots and VolcanoPlots.
Changes in version 1.1.1
Changes in version 1.6.2
Changes in version 1.11.11 (2020-10-13)
Update type: minor.
Fixed the mistake in importIsoformExpression() introduced in last updated
Changes in version 1.11.10 (2020-10-13)
Update type: minor.
Update of importIsoformExpression() fix the import of countsFromAbundance
Changes in version 1.11.9 (2020-10-12)
Update type: Minor.
More updates regarding namespace and dependencies
Changes in version 1.11.8 (2020-10-09)
Update type: Minor.
Description update regarding to namespace
Changes in version 1.11.7 (2020-09-30)
Update type: Minor.
Various documentation updates
The plotting order of the sub-plots of switchPlot() was changed to avoid problems when having long isoform names.
analyzeSignalP() was updated to be more robust at handling SignalP5 data where very few predictions were done.
Changes in version 1.11.6 (2020-09-17)
Update type: Minor.
Updated namespace.
Changes in version 1.11.5 (2020-09-14)
Update type: Minor.
Updated example code in importIsoformExpression()
Updated namespace
Changes in version 1.11.4 (2020-09-10)
Update type: Medium.
importRdata() was updated to give examples of sequence names when no overlap between fasta file and expression data was found.
importRdata() was updated to try and rescue missing gene_name annoations (must likely due to novel transcripts) and split merged genes (a problem often occuring when doing transcript assembly with tools such as Cufflinks/StringTie).
importRdata() and importCufflinksFiles() was udated with an option to print a guesstimate on the number of genes with differential isoform usage.
isoformToGeneExp() and importGTF() was updated to look for the annotation problems fixed by importRdata() and give warnings if pressent.
The example data (from individual files) was updated to include CDS.
extractGeneExpression(), a function that extracts gene level counts/expression from a switchAnalyzeRlist was introduced.
prepareSalmonFileDataFrame() and importSalmonData() was introduced. Jointly these functions enable import of Salmon data via tximeta thereby omitting the manual integration of annotation data (gtf/fasta)
isoformSwitchAnalysisPart2() was updated to only do enrichment analysis if enough events were found.
preFilter() was updated to apply the gene expression to both conditions instead of the average across all samples thereby better filtering out untrustworthy genes.
extractSplicingGenomeWide() and extractConsequenceGenomeWide() was updated to handle missing values when calculating summary statistics.
extractSplicingEnrichment(), extractSplicingEnrichmentComparison(), extractConsequenceEnrichment(), extractConsequenceEnrichmentComparison() was updated to use binom.test() instead of prop.test() as this test more apporpriate when analyzing smaller number of events.
extractSplicingEnrichment() and extractSplicingEnrichmentComparison() was updated to have more easily interpretable descriptions.
extractSwitchOverlap() was updated to also plot overlap in isoform switches and now allows for control of which venn diagrams to make.
switchPlot() was updated to only consider the dIFcutoff when classifying the “increased/decrease/unchanged usage”.
switchPlotGeneExp(), switchPlotIsoExp(), switchPlotIsoUsage() and switchPlotTranscript() was updated to enable return of the ggplot2 object (instead of printing it)
all extractConsequence() and extractSplicing() functions was updated to enable return of the ggplot2 object (instead of printing it)
switchPlotTopSwitches() was updated to also have the onlySigIsoforms argument.
Various documentation updates.
Changes in version 1.11.3 (2020-05-20)
Update type: Minor.
importRdata was updated to handle GTF files with a lot of additional information.
analyzeSignalP and analyzePFAM was updated to fix a problem with handling multiple files.
analyzePFAM was updated to attempt to handle both fixed width files and broken fixed width files.
isoformSwitchTestDEXSeq() and isoformSwitchTestDRIMSeq() was updated with the “keepIsoformInAllConditions” argument which allows data for an isoform to be kept in all comparisons even if it is only deemed significant in one comparison. TRUE by default.
importCufflinksData() was updated to handle when pathToSplicingAnalysis was not used.
Changes in version 1.11.2 (2020-05-12)
Update type: Minor.
A bug was corrected in extractSequence() which caused an error: “object ‘filterShortAALength’ not found”.
In extractSequence() the minimul length kept when using the “removeShortAAseq” argument was raised to 11 amino acids to match the pfam website.
An error in importRdata was fixed to re-enable removal of isoforms only found in annotation.
Changes in version 1.11.1 (2020-05-05)
(Version bump due to Bioconductor release).
Update type: Minor.
Update of code comments in importRdata()
Update of printed message in importIsoformExpression()
Update of analyzePFAM() to enable more robust import of fwf files with and without headers included. It also handles the mistake in pfam files with regards to the fixed width of files when the “coiled-coil” type are included.
Changes in version 1.17.2
FIX
Fix n() error from dplyr. Now importing in NAMESPACE.
Changes in version 1.17.1
FIX
Changes in version 1.31.1
Changes in version 1.0.1
Changes in version 1.0.0
Changes in version 3.46.0
New functionality
Add new function chooseLowessSpan().
fitFDist() with a non-NULL covariate
now fits a smoother
trend (with fewer spline knots) than before unless there are at
least 30 observations. This also affects squeezeVar() and
eBayes() with trend=TRUE
.
Add new argument output.style
to weightedLowess().
write.fit() now outputs a blank column heading for the row names so that the number of column names in the delimited output file will agree with the number of columns (similar to write.csv in the base package).
Code improvements
Subsetting and contrasts.fit() now work on MArrayLM objects even if the cov.coefficients component is absent.
volcanoplot() now prompts user to run eBayes() if the object doesn’t contain p-values.
Add checks and more informative error messages to getEAWP() and lmFit() when the data object is missing, NULL or has zero rows.
Subsetting for RGList, MAList, EListRaw, EList, MArrayLM or
TestResults objects now accepts arguments other than i
or j
but ignores them without an error. This is relevant if a user
adds a drop
argument by analogy with matrix subsetting.
Previously that produced an error.
Subsetting of TestResults now requires two arguments, same as all of the other data object classes listed above. Previously single index subsetting (for example object[i]) was allowed.
Improved treatment of zero weights by weighted.median().
More consistent use of rep.int(), rep_len() and rep() throughout the package.
Replace NA with NA_real_ where appropriate.
Add a message to topTableF() to warn that the function is obsolete and will be removed in a future version of limma. Remove usages of topTableF() from the User’s Guide.
Remove obsolete function toptable(), which has been officially deprecated in favor of topTable() since 1 Feb 2018.
Documentation
Revise and expand the weightedLowess help page.
Add more explanation about “heirarchical” method in the details section of the decideTests() help page.
Add Note to voom help page to emphasise that voom is not an appropriate tool to analyse expresssion measures that have been normalized for library size.
Revise the help page for plotMDS() to clarify that the function can produce PCA plots as well as PCoA plots.
Add example to EList-class help page.
Edits to the eBayes help page.
Edit concept entries for help files (for reference manual index).
Bug fixes
Revise write.fit() so that column names of the output file are
correct when digits=NULL
and the fit
object contains only
one coefficient column. Previously the same contrast name was
repeated as the column name for the coefficients, t-statistics
and p.values, making them hard to distinguish.
Bug fix to arrayWeights() when y
contains NAs, the design
matrix has several columns and some but not all genes have no
residual df.
Changes in version 2.4
Added imputation function for untargeted lipidomics datasets
Added function to boxplot enriched lipidsets related to chain length and unsaturation
Changes in version 2.0.0
Changes in version 1.3.2
Resolve issue with x labels missing from boxplots for metadata variables without levels and increase max jpgs written.
Update the check for variables with more than two levels that will require a reference provided by the user for the model and the boxplots to be more strict (ignore UNK in the level count, don’t check if it is a factor, and check to see if all of the levels are numeric to ignore continuous variables).
Fix ZINB error.
Changes in version 1.3.1
Add random effects capability to all the other non-LM models.
Add variance filtering option with default set to 0.
Normalization is now performed after filtering and N.not.zero is calculated on the untransformed space. Also includes minor edits to synchronize with the manuscript.
Add reference option required for fixed effects variables with more than two levels. Reference used in model and for boxplots.
Update heatmap to include all categorical levels.
Changes in version 3.12
BUG REPORTS
ENHANCEMENTS
NEW FUNCTIONS
DEPRECATED
Changes in version 1.9.1
Turn off the Depmap analysis in vignettes because it’s time consuming
Use count in EnrichedView when NES is not available
Changes in version 1.8.1
Update the standard gene names
Debug the color issue in the ScatterView
Remove the usage of scale_color_npg and data.table::melt from the DensitiView
Remove nPerm parameter from the enrich.GSE
Download GO-gene relationship from NCBI ftp folder
Move multiple imports to suggests
Replace view_allpath with pathview.top in FluteMLE to allow users to set the number of pathways for pathview visualization.
Changes in version 0.99.4
Renamed the class and constructor from marr to Marr on October 23, 2020.
Changes in version 0.99.3
Bioconductor single package building error
Changes in version 0.99.2
Expanded Description and changed the binwidth parameter in histograms on October 16, 2020.
Changes in version 0.99.1
Added Authors@R to the description file.
Changes in version 0.99.0
Changes in version 1.2.0
Add drop and type to generic signature of [row|col]Quantiles (<URL: https://github.com/Bioconductor/MatrixGenerics/pull/14>).
Sync API with matrixStats v0.57.0 (<URL: https://github.com/Bioconductor/MatrixGenerics/issues/17>).
Add default methods with user-friendly fallback mechanism (<URL: https://github.com/Bioconductor/MatrixGenerics/pull/16>). Suggested packages are now loaded the first time a MatrixGenerics’ generic is called (e.g. the first time MatrixGenerics::colVars() is called). With this new approach, if the user passes a dgCMatrix object and if sparseMatrixStats is already loaded, will ‘just work’ and the fallback mechanism won’t try to load anything.
Dispatch on methods for matrix objects when table objects are supplied (<URL: https://github.com/Bioconductor/MatrixGenerics/pull/15>)
Changes in version 1.15.1
BUG FIXES
Changes in version 0.99.0
NEW FEATURES
Changes in version 0.99.11
Changes
Preparations for Bioconductor release 4.0.
Removed useless datasets.
Changes in version 0.99.0 (2019-06-01)
Changes
Changes in version 0.99.0 (2020-09-11)
Changes in version 0.99.0
Changes in version 1.25.1
Unit Test bug fix
Changes in version 1.25.0
NEW function SearchNIST added (Only Windows OS)
Changes in version 1.9.1
Add several parameters to control fast version of MetaNeighbor and MetaNeighborUS
Add function to pre-train MetaNeighbor models.
Add preprocessing function to merge SingleCellExperiment objects.
Add utility functions related to meta-clusters, cluster graphs and visualization.
Changes in version 1.1.21 (2020-08-05)
NEW FEATURES
BUG FIXES
Fixed a problem with rownames when importing an existing counts table.
Changes in version 1.1.19 (2020-07-29)
NEW FEATURES
BUG FIXES
Fixed several problems with respect to custom GTF annotation import, especially when the GTF is compliant with minor GTF standards.
Fixed a few warnings resulting in errors in R>4.0.
Changes in version 1.1.18 (2020-07-03)
NEW FEATURES
Simple quantification, QC and reporting is now allowed without having to define a contrast or statistical tests to be performed.
In case of only a contrast is defined but no statistical tests required only fold changes are calculated.
BUG FIXES
Fixed undefined class/function leftovers from NOISeq integration.
Changes in version 1.1.17 (2020-06-29)
NEW FEATURES
BUG FIXES
Fixed report crash with the new readTargets wrapper function.
Changes in version 1.1.16 (2020-06-22)
NEW FEATURES
BUG FIXES
Fixed “rnacomp” plot trying to import to JSON db while not run.
Fixed report crash when “exportWhere” was NA.
Other minor bug fixes
Changes in version 1.1.15 (2020-06-12)
NEW FEATURES
BUG FIXES
Fixed annotation breaks from UCSC (rn, danRer).
Fixed crash when using excludeList (due to attributes being gone after list subsetting).
Changes in version 1.1.13 (2020-05-25)
NEW FEATURES
Addition of the harmonic mean p-value combination method (Wilson, 2019 - https://doi.org/10.1073/pnas.1814092116)
Addition of a new dataset (hg19pvalues) containing a set of gene p-values from Giakountis et al., https://doi.org/10.1016/j.celrep.2016.05.038 to be used in the main vignette as well as a playground for p-value combination
BUG FIXES
Major bug fix! The order of p-values returned by statDss was inconsistent with the rest of the stat* functions.
Other minor bug fixes.
Changes in version 1.19.0 (2020-07-02)
Changes in version 0.1.0
Changes in version 1.4.00
read_bedgraphs() supports bedgraphs files from “Bismark_cov”, “MethylDackel”, “MethylcTools”, “BisSNP”, “BSseeker2_CGmap”
write_bedgraphs() supports output to multiBed and metilene file formats
write_bigwigs() exports methrix object as bigWigs
Changes in version 1.2.10
BSgenome ref build parsing error. Issue: #24
Show which CpGs are missing when loading bedGraphs. Issue: #22
Faster HDF5 processing. PR: #21
include SeqStyle option in Manual write_bedgraphs() function. PE: #20
added the argument for SeqlevelsStyle and trackline in bedgraph. PR: #19
Changes in version 1.15.3
NEW FUNCTIONS AND FEATURES
IMPROVEMENTS AND BUG FIXES
update R requirement to (>= 3.5.0)
add extensive test for bedgraph export
update and export tests for getMethylationStats
add extensive tests for getCoverageStats
add extensive tests for normalizCoverage
update tests for getMethylDiff
Fixes #189
Changes in version 1.15.2
IMPROVEMENTS AND BUG FIXES
check.dbdir: catch if path equals root (“/”) dir
methRead:
Changes in version 2.1.2 (2020-07-01)
Core heatmap labeling improved
aggregate_top_taxa deprecated
bimodality and potential_analysis functions fixed
Changes in version 2.1.1 (2020-04-06)
Added overlap function
Changes in version 1.0.0
Changes in version 1.1.13
removed retrieve_seq and mapply_retrieve_seq function, since these need internet. Which might cause time out when check. (2020-10-16, Fri)
Changes in version 1.1.12
modified a bug in diff_analysis.phyloseq: change tax_table(ps) to ps@tax_table to avoid generate error when tax_table is NULL. (2020-10-15, Thu)
Changes in version 1.1.11
update the examples of drop_taxa. (2020-10-14, Wed)
Changes in version 1.1.10
update ggdiffclade to support data.frame input when reduce is TRUE. (2020-08-28, Fri)
Changes in version 1.1.9
update ggordpoint to fit the usage when user want to set mapping by manually. (2020-08-25, Tue)
Changes in version 1.1.8
get_taxadf, get_alltaxadf and diff_analysis has supported function datasets or other type datasets. (2020-08-17, Mon)
Changes in version 1.1.7
deprecated argument: the size argument controlled the width of line of tree has been deprecated. The linewd replace it (2020-08-14, Fri).
Changes in version 1.1.6
add inward_circular layout in ggdiffclade. (2020-08-12, Wed)
Changes in version 1.1.5
add stop information to state the class argument in diff_analysis. (2020-08-10, Mon)
Changes in version 1.1.4
add tax_table information to result of get_taxadf. (2020-08-07, Fri)
Changes in version 1.1.3
modified the angle to 90 in ggdiffclade when layout is slanted or rectangular (2020-08-05, Wed)
Changes in version 1.1.2
Changes in version 1.7.2-1.7.3
Update miRSM.R <2020-09-18, Fri>
Changes in version 1.7.1
Update module_Coexpress function <2020-08-21, Fri>
Changes in version 1.0.12
Changes in version 6.14.0
new features / enhancements / changes
bug fixes
Changes in version 0.99.0
Changes in version 0.99.0
Changes in version 1.33.14
remove reverse complement alignment for RNA motifs.
Changes in version 1.33.13
narrow the predefined font.
Changes in version 1.33.12
fix the issue for pcm2pfm if the column counts are not identical.
Changes in version 1.33.11
update the markers to allow label + line/rect.
Changes in version 1.33.10
add alignment function for AA motifs.
Changes in version 1.33.9
fix the issue for AA motif of clusterMotifs
Changes in version 1.33.8
fix the issue of symbol position for predefined font
Changes in version 1.33.7
update check ghostscript
Changes in version 1.33.6
fix the bug in pcm2pssm
Changes in version 1.33.5
fix the bug in pcm2pssm
Changes in version 1.33.4
add pssm class
Changes in version 1.33.3
replace MotIV by matalign.
add cutoffPval for motifSignature function.
Changes in version 1.33.2
add parameter environment for coloredSymbols
Changes in version 1.33.1
change grImport, grImport2 and MotIV to Suggests.
use roxygen2 to generate help files.
Changes in version 0.99.9 (2020-08-23)
Check package bugfix in getURL function
Changes in version 0.99.8 (2020-08-13)
Getter/Setter for URL of backend server
Changes in version 0.99.7 (2020-06-08)
Updated database
New authors
Changes in version 0.99.1 (2020-05-22)
Updated .gitignore
Changes in version 0.99.0 (2020-05-21)
Submission to Bioconductor
Changes in version 0.1.0 (2020-05-04)
Creation
Changes in version 1.21.1
changed msaClustalW() examples to run smoothly on Windows with R 4.0.x
added warning to msaClustalW() help page regarding cluster=”upgma” on Windows
Changes in version 1.21.0
new branch for Bioconductor 3.12 devel
Changes in version 1.1
Changes in 1.1.7
Changes in 1.1.6
Changes in 1.1.5
Changes in 1.1.4
Changes in 1.1.3
Changes in 1.1.2
Changes in 1.1.1
Add some popular distance/similarity metrices: ndotproduct neuclidean navdist nspectraangle; see also PR #33.
Add deprecation note to dotproduct <2020-05-22 Fri>.
Changes in 1.1.0
Changes in version 0.99.0
Changes in version 0.99.26
update doc for msImpute
Changes in version 0.99.25
fix typo in msImpute man page
Changes in version 0.99.24
Bug fix in the internal function l2bary
Changes in version 0.99.23
selectFeatures and msImpute now use information theoretic approaches to find informative features for MAR/MNAR diagnosis and estimation of optimal rank, respectively.
lambda in msImpute is now estimated from the data, using the bayesian interpretation of this shrinkage operator.
msImpute can be run in three modes: “v1” is the original implementation of softImpute-als algorithm, “v2” is the enhanced low-rank estimation implemented in this version update, “v2-mnar” is adaptation of low-rank models for MNAR data. More details about methods in documentation.
Changes in version 0.99.22
Submitted to Bioconductor
Changes in version 2.15
Changes in 2.15.7
Changes in 2.15.6
Changes in 2.15.5
Changes in 2.15.4
Changes in 2.15.3
Changes in 2.15.2
Changes in 2.15.1
Changes in 2.15.0
Changes in version 0.99.0 (2020-10-02)
Changes in version 1.15.1
Update dev to match bug fixes in master
Changes in version 1.14.1
Update of rdpc algorithm (see https://github.com/computational-metabolomics/msPurity/issues/78)
Update of align algorithm (see https://github.com/computational-metabolomics/msPurity/issues/79)
Fix for spectralMatching of type ‘scan’ previously incorrectly outputing no matches
Changes in version 0.99.0
Added vignette.
Changes in version 0.0.1
Changes in version 0.99.0 (2020-09-28)
Changes in version 1.6.6 (2020-10-13)
Fix the bug in converters due to fractions with same mean, sum and max values
Fix the bug in converters due to summaryforMultipleRows
Fix the bug in OpemMS converter due to duplicated rows
Changes in version 1.6.3 (2020-06-05)
Allow NA in the annotation file
Changes in version 1.6.2 (2020-06-02)
Fix the bug in proteinSummarization() function and make sure the input to dataProcess is data.frame
Changes in version 1.6.1 (2020-05-10)
Update groupComparisonTMT() to make predictions for every protein
Changes in version 0.99.0 (2018-09-21)
Changes in version 1.16.0
New features
Bug fixes and minor improvements
Changes in version 0.99.0 (2020-04-24)
Changes in version 0.99.0
Changes in version 1.7.1 (2020-08-28)
Track NEWS
Bump version
Update R version dependency from 3.5.0 to 4.0
Add exported objects to NAMESPACE that caused BiocCheck error
Add CITATION, also to README.md file
Update DESCRIPTION o Add Mikhail Dozmorov as Maintainer o Add URL and BugReports fields
Changes in version 0.99.10 (2020-10-02)
PRE-RELEASE
Changes in version 1.0.0
Changes in version 1.5.1 (2020-05-04)
Changes in version 0.99.9 (2020-10-01)
Reverted changes introduced in 0.99.6
Set SSL security level to 1 in Linux environment to bypass a bug in OpenSSL 1.1.1
Changes in version 0.99.6 (2020-09-29)
Changed all URLs to http to prevent issues when accessing websites via HTTPS due to a bug in OpenSSL 1.1.1
Changes in version 0.99.4 (2020-09-07)
Introduced changes suggested during Bioconductor review
Changes in version 0.99.0 (2020-07-24)
Submitted to Bioconductor
Changes in version 0.99.94
Color scale based now on scale_color_viridis_c()
Changes in version 0.99.93
Stable version for bioconductor release
Changes in version 0.99.92
Sets up BiocCheck requirements
Changes in version 1.1.4
Changes
somatic mutations
Changes in version 0.99.5 (2020-09-08)
Modification to optimd function to prevent decreasing of the likelihood function when appling mini-batch with commonwise dispersion
Changes in version 0.99.0 (2020-09-08)
Submit to bioconductor
Changes in version 0.2.0 (2020-09-07)
Matrix and Delayed array framework complete running
Changes in version 1.5.5
Added importSJ for importing SJ.out.tab files from the aligner STAR
Added plotType = “residuals” for plotSeqContent()
Changes in version 1.5.4
Allowed for ignoring basename() calls in all importNgsLogs functions
Added cumulative GC plot to plotGcContent() as plotType = “cdf”
Changed plotting option name from cumulative to cdf for plotSeqLengthDistn()
Announced deprecation of runFastQC()
Changes in version 1.5.3
Fixed bug in plotOverrep
Changes in version 0.99
Initial release to Bioconductor.
Added NEWS file.
Changed image paths in vignette.
Changes in version 1.99.0 (2020-10-03)
Preparation for Bioconductor 3.12
Changes in version 1.3.4 (2020-08-04)
Can be directed to different server by options
Changes in version 1.3.1 (2020-06-05)
Changes in version 2.19.2 (2020-06-03)
Updated ctb: added Magellan and exprTk and clarified contributions.
Changes in version 2.19.1 (2020-05-05)
Occasional failures of @test.sample-prob.R#42 in Windows 386
Changes in version 2.19.0 (2020-05-05)
Bumped version to match current Biocdevel.
Changes in version 1.8.0
MODIFICATIONS
harmonised inputs to algorithms
added unit tests
updated authors
Changes in version 3.11
Enhancements
Bug Fixes
Added a fix to the density estimate used by gate_tautstring
Changes in version 3.10
API Changes
Simple renaming
Classes and methods no longer exported
Bug Fixes
Changes in version 1.32.0
BUG FIXES
Changes in version 1.7.1
Move to S3/S4 methods to be compatible with FRASER
Due to the S3/S4 changes minor changes in the argument names happend mainly ods -> object or x
Bugfixes: #29
Changes in version 0.99
Substantial changes to prepare for Bioconductor submission o added S4 classes / methods / generics o integration with MultiAssayExperiment
Changes in version 0.1 (2020-01-09)
Initial development version
Changes in version 0.99.0 (2020-09-21)
Changes in version 1.4.1 (2020-04-30)
Changes in version 1.29.1
developmental version now available on GitHub at: https://github.com/datapplab/pathview
fixed warning on “requireNamespace(pkg.name)” in geneannot.map.R and sim.mol.data.R. Now “import” from org.Hs.eg.db, instead of “suggest” it. Also import more functions and class from AnnotationDbi.
prevented potential error caused by class(exprs) == “data.frame” or “class()==” if conditions in multiple functions. class(exprs) now returns a vector of length 2, which caused the error.
Changes in version 2.16.0
Other notes
Changes in version 2.2.0
added support to overlay variable loadings arrows on biplot
better positioning of PC labels in triangular pairs plot
added functionality to encircle groups of samples
added functionality to draw stat ellipses with confidence intervals
users can now add legend titles and these will be added by default
Changes in version 1.3.4 (2020-10-23)
Add missing function export for GUI
Changes in version 1.3.3 (2020-10-11)
Shiny Graphical User Interface
Changes in version 1.3.2 (2020-09-29)
Unittest numerical precision correction for Ubuntu 20.04.1 LTS
Changes in version 1.3.1 (2020-09-21)
Retention time correction procedure based on reference compounds
Exponentially Modified Gaussian (EMG) peak fitting
Changes in version 1.7.1 (2020-07-21)
BUG CORRECTION
Changes in version 0.3.2
IMPORTANT:
Implemented data-raw for reproducibility
MINOR:
Changed xlim of norm. distr. plot in plotPeriodicityResults()
Changes in version 0.3.1 (2020-05-05)
IMPORTANT:
Added ggplot2 theming
MINOR:
Created a utility char2BSgenome()
Changes in version 0.3.0 (2020-05-03)
Added vignette
Changes in version 0.2.1 (2020-03-04)
Changes in version 1.19.1
Changes in version 1.9.5
Support for preloaded sessions
Changes in version 1.9.3
Changed Dockerfile to nginx+rApache (default ports are changed)
Changes in version 2.1.12
Changes in version 0.1.5
Changes in version 1.3.11
Add filter number of co-orthologs to parseInfoProfile()
Changes in version 1.3.10
Calculate percentage of present taxa after filtering of var1 and var2
Fixed filter when working with high taxonomy ranks
Changes in version 1.2.8
Added new NCBI taxonomy ranks (e.g. biotype, isolate, pathogroup, …)
Added function to reset taxonomy data
Changes in version 1.2.7
Solved problem with new NCBI taxonomy rank “clade” by replace them with “norank”
Changes in version 1.2.6
Fixed bug customized profile of subset of taxa not clickable
Changes in version 1.2.4
Fixed bug checking invalid taxon IDs
Changes in version 1.2.1
Fixed bug in rankIndexing and processNcbiTaxonomy
Improved check for invalid input taxon IDs
Changes in version 1.15.20 (2020-09-28)
Changes in existing functions
When automatically computing the threshold in the consensus function, we now do not allow it to be more than 1 to be compatible with bnlearn 4.6.1.
Changes in version 1.15.16 (2020-09-22)
Changes in existing functions
The modules can now be determined in the module.heatmap function using the new mes argument.
Changes in version 1.15.14 (2020-09-08)
Bug Fixes
combine.networks now really removes the big TOM file when doRemoveTOM=TRUE.
Changes in version 1.15.12 (2020-06-22)
Changes in existing functions
Bug Fixes
Changes in version 0.99.43 (2020-07-20)
there is now the possibility to continue runs despite errors, and enlarged merging capacities
Changes in version 0.99.27 (2020-04-29)
the plotting functions for the scRNAseq clustering pipeline
(scrna_evalPlot_DR
and scrna_evalPlot_clust
) have been replaced
by more flexible, pipeline-generic functions (evalHeatmap
) and a
silhouette-specific plotting function (scrna_evalPlot_silh
). The
general heatmap coloring scheme has also been changed to make
meaningful changes clearer.
Changes in version 0.99.23 (2020-04-21)
Added SVA-DEA pipeline and vignette
Standardized results heatmaps for any PipelineDefinition
Changes in version 0.99.7 (2020-04-01)
Submitted to Bioconductor
Changes in version 0.99.3 (2020-02-07)
made important changes to the scRNAseq pipeline, greatly simplifying the format of the output. As a consequence, results produced with older version of the package are not anymore compatible with the current version’s aggregation and plotting functions.
Changes in version 1.9.3
@PeteHaitch corrected table layout in vignette
Changes in version 1.9.2
minor documentation fixes
Changes in version 1.9.1
Changes in version 1.99.3
NB function now exported
note that version 1.99.3 on GitHub was version 1.1.0 on Bioconductor.
Changes in version 1.99.2
bug fix in fragment generation (last 2 bases of transcript were never sequenced)
Changes in version 0.99.45
The elbow method to calculate the optimum number of clusters has been added in PomaClust function
Changes in version 0.99.37
Bioconductor logo
Changes in version 0.99.33
POMA EDA vignette added
Changes in version 0.99.16
pkgdown files removed from master branch
Changes in version 0.99.0
Changes in version 0.99.6 (2020-08-30)
Major simplification of the preciseTAD function, many arguments are kept default
Major vignette rewrite
Add pkgdown web site
Update DESCRIPTION o Package description
Start tracking NEWS
Changes in version 0.99.4 (2020-07-14)
Preparing for release
Changes in version 0.99.0 (2020-06-16)
Initial version
Changes in version 0.99.0
Changes in version 1.3
Changes in version 2020-10-14 (2020-10-14)
Model matrices are not accessed in the local and not in the global enviroment
Changes in version 2020-09-01 (2020-09-01)
Fixed issue with rownames when using Progeny with Permutations function
Changes in version 2020-06-09 (2020-06-09)
Website: Google Analytics
Changes in version 2020-04-27 (2020-04-27)
PROGENy website development
Major update with the following main points:
Added the mouse model matrix containing 14 pathways
The human model matrix extended to 14 pathways
Added the following functions: progenyPerm, progenyScatter, progenySavePlots, getModel
Added tests and test data
Added the vignette for usage the PROGENy on single-cell RNA-seq data
Added functionality to work with Seurat objects
Changes in version 1.99
CHANGES IN VERSION 1.99.2
CHANGES IN VERSION 1.99.1
Changes in version 1.14.4
Copy-edit tutorials on loading user-provided data and using the command-line version
Changes in version 1.14.3
Fix unit tests due to changes in Ensembl API response
Changes in version 1.14.2
Support for loading more data formats
New features
Bug fixes and minor changes
Fix comparing signed and unsigned integers in Rcpp functions
Changes in version 1.14.1
Fix unit tests for R 4.0
Changes in version 1.20.0
NEW FEATURES
Support for GATK4 GenomicsDB import for mapping bias calculation
Added –additionaltumors to PureCN.R to provide coverage files from additional biopsies from the same patient when available
PSCBS segmentation now identifies on-target breakpoints first when off-target is noisy, thus boosting sensitivity in on-target regions
Beta-binomial model in runAbsoluteCN now uses the fits in mapping bias database. We plan to set this as default in upcoming versions and appreciate feedback.
SIGNIFICANT USER-VISIBLE CHANGES
We now check if POP_AF or POPAF is -log10 scaled as new Mutect2 versions do.
Added support for GERMQ info field containing Phred-scaled germline probabilities.
Detect Mutect2 VCF more reliably
Updated Mutect2 failure flags: “strand_bias”, “slippage”, “weak_evidence”, “orientation”, “haplotype”
Removed defunct normal.panel.vcf.file from setMappingBiasVcf
Removed defunct interval.weight.file from segmentationPSCBS, segmentationCBS and processMultipleSamples
Made calculateIntervalWeights defunct
Changed default of min.normals in calculateMappingBiasVcf/Gatk4 to 1 from 2
Changed default of –signature_databases to “signatures.exome.cosmic.v3.may2019” (v3 instead of v2)
Now warn if recommended -funsegmentation is not used
Added parallel option for callAmplificationsInLowPurity
callMutationBurden now uses all non-filtered targets as callable region when callable is not provided
plotAbs in chromosome mode now displays wider range of log2 ratios (makes it possible to examine outliers)
Moved vcf.field.prefix from predictSomatic to runAbsoluteCN since it now adds more fields like prior somatic and mapping bias to the VCF
Changed default of runAbsoluteCN min.ploidy to 1.4
BUGFIXES
Fix for crash with CNVkit input when log-ratio contained highly negative outliers
Fixed a bug in preprocessIntervals/IntervalFile.R when input contained overlapping and stranded intervals
Fix for crash when GC-correction is attempted on empty coverage (for example off-target region without any off-target reads)
Fix for crash when VCF FA field contained missing values
Fix for a bug in callAmplificationsInLowPurity that can cause a wrong chromosome percentile
Changes in version 0.99
QFeatures 0.99.4
QFeatures 0.99.3
QFeatures 0.99.2
QFeatures 0.99.1
QFeatures 0.99.0
Changes in version 1.7.3
Fix limits of scale in corrPlot to c(0, 1)
Fix bug in regress intensities where control columns were not being removed
Changes in version 1.7.1
Change Vignette to HTML
Add textsize argument to corrPlot
Allow missing values in scaling normalisations
Changes in version 1.30.0
NEW FEATURES
Changes in version 1.0.1
Harmonize function and API design to be in line with PharmacoGx R package
Changes in version 1.0.0
Changes in version 1.14.0
Bug fixes and minor improvements
Changes in version 1.1.1 (2020-09-23)
Function contrastModel() added to support contrast rotation
Vignette extended
Deprecate function df_estimate()
Changes in version 2.29.1
Changes in version 2.10.0
Refactored getNetworkViewSuid
Handled special 404 cases in .cyError
Bug fix #94: added base.url param
Changes in version 1.3.6 (2020-09-01)
Improved analyse_sc_clusters for SingleCellExperiment objects to define cell grouping using factors and a single character string specifying the metada field.
Changes in version 1.3.4 (2020-09-01)
Fixed bug in analyse_sc_clusters when processing SingleCellExperiment objects.
Changes in version 1.3.3 (2020-05-26)
Updated documentation
Changes in version 1.3.2 (2020-05-26)
Added workaround for SEC_E_ILLEGAL_MESSAGE error on older Windows systems.
Changes in version 1.3.1 (2020-04-29)
Added option to hide non-significant pathway in plot_correlations
Changes in version 1.1.2
Random tiebreaking is by default off for reconsi(), but on for testDAA()
Changes in version 1.1.1
Changes in version 0.99.0
NEW FEATURES
Changes in version 0.99.0
Added getdb functions for database file download and load
Added servermatrix function to get latest database file metadata
Added User’s Guide and Data Analyses vignettes
Added metadata and data_analyses.RData to /inst/extdata
Changes in version 0.01
Added key query/accessor functions.
Added package vignette.
Changes in version 1.17.1 (2020-05-03)
NEW FEATURES
New annotation based on an SQLite database. Rebuild must be performed otherwise the application will break. Download of a ready made annotation is also available (see vignette).
More supported genomes
Quick, high-level profile based on RPM instead of coverage
Speed and code improvements
BUG FIXES
Changes in version 0.99.19
Fix bugs in .regSEA function.
Changes in version 0.99.18
Update R version dependency to 4.0.0.
Changes in version 0.99.17
Use Authors@R [cre] designation.
Changes in version 0.99.16
Import magrittr
Changes in version 0.99.15
Reexport pipe %>%.
Changes in version 0.99.14
Replace bplapply by lapply in pickSoftThreshold2 function.
Changes in version 0.99.13
Remove doParallel package from imports.
Changes in version 0.99.12
Remove .Rpoj file.
Changes in version 0.99.11
The show methods for DeaSet, TopNetwork, Enrich, Score, and RegenrichSet object have been optimized.
Changes in version 0.99.1
Changes in version 1.23.2
SIGNIFICANT USER-VISIBLE CHANGES
Changes in version 1.1.3
SIGNIFICANT USER-VISIBLE CHANGES
DOCUMENTATION UPDATES
roxygen version update was included and documentation was build under the new roxygen version.
Changes in version 1.1.1
SIGNIFICANT USER-VISIBLE CHANGES
Changes in version 1.0.0
Changes in version 1.1.10 (2020-10-13)
Added missing item (alignmentEndPositionQuery) to the output list in the documentation of rfamSequenceSearch
Changes in version 1.1.9 (2020-10-13)
Fixed a bug that caused sequence searches with sequences longer than 10000 bases to crash
Changes in version 1.1.6 (2020-10-01)
Set SSL security level to 1 in Linux environment to bypass a bug in OpenSSL 1.1.1
Changes in version 1.1.5 (2020-09-30)
Reverted changes introduced in 1.1.4
Changes in version 1.1.4 (2020-09-29)
Changed all URLs to http to prevent issues when accessing websites via HTTPS due to a bug in OpenSSL 1.1.1
Changes in version 1.1.3 (2020-07-18)
Fixed a bug that caused sequence searches to crash when applying clan competition filter and no associated clan was found for some Rfam families
Changes in version 1.1.2 (2020-07-15)
Fixed a bug that caused sequence searches to crash when applying clan competition filter and a match was found in the - strand
Changes in version 1.1.1 (2020-07-08)
Added the possibility to filter hits of a sequence search by clan competition
Sequences larger than 10000 nucleotides can now be provided as input for sequence-based searches of the Rfam database
Changes in version 1.21.1
Changes in version 1.21
changing some less than signs to less than or equal to, to ensure we get results.
planning a refactor to handle other gene ID systems and example datasets. not done
Changes in version 2.34.0
NEW FEATURES
Added support for read access to files in Amazon S3 buckets (currently only available on non-Windows platforms).
Included read and write support for dynamic compression filters distributed in rhdf5filters.
CHANGES
BUG FIXES
Fix bug in H5Dget_storage_size() where the wrong C function was called.
NA values in logical datatypes are now preserved when written and read back into R (https://github.com/grimbough/rhdf5/issues/58).
Fixed error when trying to write a vector containing only empty strings (https://github.com/grimbough/rhdf5/issues/60).
h5ls() and h5dump() no longer crash when given a file containing recursive or duplicated groups (https://github.com/grimbough/rhdf5/issues/48).
Reading compound datasets with at least one 8-bit integer field now works (https://github.com/grimbough/rhdf5/issues/71).
Fixed problem when writing a data.frame containing a column of raw values. These columns were ommitted when creating a compound dataset.
Patch early UNPROTECT() when reading a Enum type that could cause a segmentation fault (https://github.com/grimbough/rhdf5/issues/73)
Changes in version 1.2.0
BUG FIXES
Changes in version 1.1.6
fix the issue in shiftReads for reads width and readsEndPlot for seqlevels.
Changes in version 1.1.5
Update documentation about the R version requirement.
Changes in version 1.1.4
Update authorship.
Changes in version 1.1.3
Fix the error “CIGAR is empty after qnarrowing”.
Changes in version 1.1.2
update plotTranscript to give more informative warning message.
Changes in version 1.1.1
Changes in version 1.1.2 (2020-09-20)
Added citation and README
Changes in version 1.1.1 (2020-06-24)
Replaced “DESeq” with “DESeq2” throughout the package
Changes in version 0.99.1
2020-10-01
Added rnaEditr.Rproj into .gitignore to fix the building error.
Changes in version 0.99.0
2020-09-22
We are planning to submit to Bioconductor by this Friday, and here is the link to the issue on gitlab where we resolve BiocCheck() ERRORs, WARNINGs, and NOTEs: https://gitlab.com/Jennyzly2016/rnaEditr/-/issues/64
Changes in version 1.3.5 (2020-08-30)
bugfix for GRangesList as annotation data. Only non-overlapping elements are allowed
Changes in version 1.3.1 (2020-04-29)
added stats function to access details about number of reads used for analysis
Changes in version 1.99.2 (2020-10-22)
BUG FIXES
Changes in version 2.7.1
Changes in version 2.17
CHANGES IN VERSION 2.17.4
CHANGES IN VERSION 2.17.3
CHANGES IN VERSION 2.17.2
CHANGES IN VERSION 2.17.1
CHANGES IN VERSION 2.17.0
Changes in version 1.99.01
no bug, but removed extra files from man folder
Changes in version 1.1.12
Changes in version 1.1.3
Warn user when no scores are provided and thus falling back to term’s size as the score to rank terms
Changes in version 1.1.2
Fix bug that would break reduceSimMatrix()
when no scores were
provided
Changes in version 1.5.1
USER VISIBLE CHANGES
Updated citation
An error is returned if there are duplicated sample names in the expression data
Changes in version 0.99.0
Changes in version 2.4.0
The ‘isPairedEnd’ parameter in featureCounts() is now used to check if the type of input reads (paired-end or single-end) is correctly specified.
A new parameter ‘countReadPairs’ was added to featureCounts to specify if read pairs should be counted for paired-end read data.
Changes to the input parameters and output of cellCounts() function. CellCounts will generate a Sample Sheet for samples included in the scRNA-seq data, based on the sample index set name provided by the user. Structure of the List object returned by cellCounts() is also simplified. cellCounts() now also outputs a BAM file and a gzipped FASTQ file including raw reads for each sample.
Changes in version 2009-07-13
combineRTCA(list): Additional column is renamed into Plate. The vlues is evaluated from list item names. When the list has no name, an integer index beginning from 1 is used. Special attentions to list partially with names is noted in the documentation.
parseRTCA(file, dec=”.”,phenoData, skipWell,…): Example is added in the documentation how to import pre-configured phenoData. Details section in the documentation is re-written to describe the process of parsing.
RTCA-class: Experiment ID added to RTCA class
Makefile: add Makefile to simplify common tasks like check and install
plotGridEffect: takes ‘column’ instead of ‘col’ as mode parameter, and renders the mode as the title of the legend. Documentation updated.
plotRTCA: is removed from the package and is substituted by the plot function.
Changes in version 2.20.0
New features
Bug fixes and minor improvements
Changes in version 0.99.2 (2020-06-05)
Changes in version 1.10.0
Defuncted getColoredPathway
Doc fix: examples fixed and sample gmt included
Changes in version 1.8.5
Doc fix: added reference to clusterProfiler
Changes in version 1.8.4
Doc fix: fixed Pathway Analysis vignette
Changes in version 1.8.3
Bug fix: GMT parsing #16
Changes in version 1.8.2
Doc fix: vignette with BridgeDbR
Bug fix: fixed rjson replacement
Changes in version 0.28.0
SIGNIFICANT USER-VISIBLE CHANGES
Replaced DataTable class with RectangularData class.
Replaced DataTable_OR_NULL with DataFrame_OR_NULL class.
Add parallel_slot_names() generic and methods for Vector derivatives. This replaces vertical_slot_names(). The concept of “vertical” and “horizontal” slots is now a RectangularData concept only i.e. only RectangularData derivatives should define vertical_slot_names() and horizontal_slot_names() methods. For RectangularData derivatives that are also Vector derivatives, one of the two methods should typically be defined as a synonym of parallel_slot_names(). For example horizontal_slot_names() now returns parallel_slot_names() on a DataFrame derivative and vertical_slot_names() will return parallel_slot_names() on a SummarizedExperiment derivative.
makeClassinfoRowForCompactPrinting() is now exported.
showAsCell() now trims strings that are > 22 characters.
Small tweak to show() method for Rle objects. Now it uses showAsCell() instead of as.character() for more compact display of the run values of the Rle object, and for consistency with other show() methods (e.g. with method for DataFrame objects).
DEPRECATED AND DEFUNCT
BUG FIXES
Fix coercion from SimpleList to DataFrame.
Fix bug in showAsCell() on ordinary data frames.
Make sure showAsCell() works on a list of non-subsettable objects.
Changes in version 1.3.3
set-based tests: burden, ACAT-V
Changes in version 1.2.2
update the citation
work around gcc-10
Changes in version 0.99.1
Base class: SangerReads is designed to store each forward/revers reads.
Changes in version 0.1.0
Project starts.
Changes in version 1.0.0
Changes in version 0.99.31
Added extra filtering for barnyard data (a mixture of multiple species).
Changes in version 0.99.30
Added thresholding of number of top genes to use in testing steps. This avoids high number of false positives in ultra-high dimensional datasets, e.g. 10x barnyard data.
Changes in version 0.99.29
Updated functions of calculating Pearson correlation in sparse matrix. New functions are more accurate.
Changes in version 0.99.25
Changed R dependency back to 4.0.0.
Changes in version 0.99.24
Changed vignette title to match the citation.
Changes in version 0.99.23
Minor edit of README.md
Changes in version 0.99.22
Changed output of CB2FindCell to be an SummarizedExperiment object. Changed GetCellMat accordingly. Changed examples and testthat accordingly.
Changes in version 0.99.21
Minor bug fix in Read10xRaw.R. Added as.numeric when building sparse matrix.
Changes in version 0.99.20
Updated citation.
Changes in version 0.99.19
Minor edits on package vignettes.
Changes in version 0.99.18
Minor edits on package vignettes.
Changes in version 0.99.17
Initial version preparing to submit to Bioconductor.
Changes in version 0.99.16
Added a quick function QuickCB2 by combining all necessary functions into one. Input: directory of raw data. Output: filtered matrix, or a Seurat object containing filtered matrix.
Changes in version 0.99.15
When dividing barcodes into groups with similar barcode counts, the last group will be combined with second last group if the number of barcodes in the last group is less than half of that in the second last group.
Changes in version 0.99.14
Change parameter names to match those in the paper: retain -> upper. background -> lower.
Changes in version 0.99.13
Bug fix when retain threshold is larger than any barcode.
Changes in version 0.99.12
Baseline (2 * background) clustering threshold will be printed out.
Changes in version 0.99.11
Minor bug fixes when there is no cluster.
Changes in version 0.99.0
Changes in version 1.0.0
Changes in version 1.3.25 (2020-10-26)
scDblFinder has important improvements on speed, robustness and accuracy
in additional to doublet calls, scDblFinder reports the putative origin (combination of clusters) of doublets
Changes in version 1.3.19 (2020-08-06)
scDblFinder now hosts the doublet detection methods formerly part of
scran
Changes in version 1.13.1 (2020-08-17)
Changes in version 0.99.0 (2020-08-13)
Changes in version 0.99
scp 0.99.4
scp 0.99.3
scp 0.99.2
scp 0.99.1
scp 0.99.0
Changes in version 1.3.10 (2020-10-16)
Implementing suggested improvements from Aaron Lun
Changes in version 1.3.9 (2020-10-12)
scPCA now accepts DelayedMatrix objects as target and background datasets.
Changes in version 1.3.8 (2020-09-01)
Minor bug fixes
Changes in version 1.3.6 (2020-08-30)
Users can now pass factors and character vectors to the clusters argument.
Changes in version 1.3.5 (2020-08-18)
Included argumetns in scPCA to control RSpectra::eigs_sym convergence: error tolerance and max number of iterations
Changes in version 1.3.4 (2020-08-12)
In future updates, we’d like to explore using the DelayedArray framework to support the analysis of larger datasets.
Changes in version 1.3.3 (2020-08-08)
Users can now pass in their own cluster labels
Changes in version 1.3.2 (2020-08-05)
Changes in version 1.18.0
Deprecated coassignProbs() as this is replaced by bluster::pairwiseRand()
Deprecated boostrapCluster() as this is replaced by bluster::bootstrapStability().
Deprecated gene.names= in the various pairwise* functions as being out of scope.
Added the testLinearModel() function to obtain inferences from a linear model.
Modified pseudoBulkDGE() to use formulas/functions in the design= argument. Allow contrast= to be a character vector to be run through makeContrasts().
Added the pseudoBulkSpecific() function to test for semi-label-specific DEGs in pseudo-bulk analyses.
Added the summaryMarkerStats() function to compute some basic summary statistics for marker filtering.
Modified row.data= in findMarkers() to support list inputs. Added a add.summary= option to easily include summary information.
Modified combineVar() and combineCV2() to support list inputs.
Deprecated doubletCells() as this is replaced by scDblFinder::computeDoubletDensity().
Deprecated doubletCluster() as this is replaced by scDblFinder::findDoubletClusters().
Deprecated doubletRecovery() as this is replaced by scDblFinder::recoverDoublets().
Added sparse-optimized variance calculations to modelGeneVar(), modelGeneCV2() and related functions, which may result in slight changes to the results due to numeric precision.
Exported combineBlocks() to assist combining of block-wise statistics in other packages.
Added lowess= and density.weights= options to fitTrendVar() to rescue overfitted curves.
Raised an error in denoisePCA() upon mismatches in the matrix and technical statistics.
Changes in version 1.2.3
Changed the access of the sample data to github.io repo: readRDS(url(“https://ncborcherding.github.io/vignettes/scRepertoire_example.rds”))
Changes in version 1.2.2
Removed Startrac-based functions in order to pass build on Bioconductor. DEPRECATED AND DEFUNCT
Deprecate StartracDiversity()
Changes in version 1.2.0
SUBMITTED
SIGNIFICANT USER-VISIBLE CHANGES
DEPRECATED AND DEFUNCT
Deprecate combineSeurat in favor or combineExpression().
Deprecate seurat2List in favor of expression2List().
Changes in version 0.99.18
Updated author information in the vignette
Changes in version 0.99.17
Updated NEWS formatting
Edited DESCRIPTION to SingleCellExperiment R package
Updated information in the vignette
Changes in version 0.99.16
Added getCirclize()
Changes in version 0.99.15
Modified numerator for index function
Changes in version 0.99.14
Removed bracket from indexing function
Changes in version 0.99.13
Added exportTable to remaining viz functions
Modified morisita index to correct error
Changes in version 0.99.12
Reducing the size of the screp_example to fulfill < 5 mB requirement. Randomly samples 100 cells and removed RNA counts from Seurat object
Changes in version 0.99.11
Updated compareClonotype to allow for clonotype comparisons
Changes in version 0.99.10
Bioconductor did not detect the version update.
Changes in version 0.99.9
Bioconductor had no love - changed the Seurat package to imports instead of required, see if that will address the compiling issue that results in a killed: 9 error.
Changes in version 0.99.8
Passed checks on system, let’s see how much bioconductor hates it
Changes in version 0.99.7
But really this time, changed the colData import
Changes in version 0.99.6
Changed colData import
Changes in version 0.99.5
Added screp_example data to package
Added visVgene function for visualizing the distribution of V genes in TCR
Added support for monocle to combineExpression function
Updated documentation for combineTCR() and combineBCR()
Updated documentation to utilize SingleCellExperiment formats
Updated Vignette to utilize SingleCellExperiment formats
Added Author information to vignette
Add intro and conclusion to vignette
Removed html knitted vignette
Removed descriptive code snippets
Changes in version 0.99.4
Modified expression2List() to allow for variables across meta data
Changes in version 0.99.1
Changed R (>= 3.6) to R (>= 4.0)
Changes in version 0.99.0
Changed DESCRIPTION version to 0.99.0
Removed file seurat_example.rda, accidentally committed
Deleted git attributes
reduced Seurat object size for alluvialClonotype in vignette
Changed the alluvialClonotype assessment to account for only 1 condition
Changes in version 2.0.0
Extended to use the version 2.0.0 of LRBase.XXX.eg.db-type packages
Omitted typing Enter-key many times to perform example(‘cellCellReport’)
lr.evidence option was added in cellCellRanks() and cellCellDecomp() to select ligand-receptor databases to construct CCI-tensor (cf. Evidence code: https://github.com/rikenbit/lrbase-workflow)
The L-R evidence was embeded in the HTML report.
The bug related to the hyper-link was fixed in .hyperLinks.
Auto library installation/loading for MeSH.XXX.eg.db. Note that this function is based on the NCBI Taxonomy ID embedded in METATDATA table in the sqlite3 file of LRBase.XXX.eg.db.
The order of the parameters of cellCellSetting were changed as cellCellSetting(sce, lrbase, label, lr.evidence=”all”, color=NULL), and color parameter was changed as a optional parameter. If it is not specified, the color is automatically selected.
The way to specify the celltype label was changed in cellCellSetting.
The vignettes were modified.
The convertNCBIGeneID is deprecated. The same functionality can be available as scTGIF::convertRowID instead.
Changes in version 1.4.1-3
A bug was fixed in .cellCellDecomp.Halpern()
Changes in version 1.2.1
Changes in version 1.0.0
Split off scuttle from scater by migrating all non-visualization code from the latter.
Began transition to dot-separate argument names from original snake case format.
Added a geometricSizeFactors() function, deprecated geometric=TRUE in librarySizeFactors().
Single-object downsampling in downsampleBatches() now behaves more consistently with multi-object downsampling.
Changes in version 1.9.2
update description for single-cell data in reference manual.
Changes in version 1.9.1
add example for single-cell data.
Changes in version 1.14.0 (2020-05-05)
Changes in version 1.29.2
UTILITIES
show a warning when an unsorted index is used in seqSetFilter()
show a message if seqVCF_Header()
fails
a new option ‘chr_prefix’ in seqGDS2VCF()
BUG FIXES
seqVCF_Header()
fixes ‘contig’ in the header of VCF if there are
different fields
Changes in version 1.28.1
BUG FIXES
seqRecompress(, verbose=FALSE)
works correctly
seqSetFilter(, action="push+set")
should not reset the filter
before setting a new filter
Changes in version 0.99.3 (2020-09-18)
Updated vignette and documentation regarding SummarizedExperiment
Updated NAMESPACE regarding SummarizedExperiment
Changes in version 0.99.2 (2020-09-08)
Changed code to take SummarizedExperiment objects as input and output
Changed tests for this new code
Changes in version 0.99.1 (2020-09-01)
Added BugReports field to the DESCRIPTION file
Fixed typo in checkForReplicates function name
Replaced cat by message, warning or stop
Suppressed unappropriate keywords (e.g., ERROR, WARNING) in messages
Replaced external datasets by generated datasets in tests
Suppressed rm(list=list()) in tests
Changes in version 0.99.0 (2020-07-09)
Submitted to Bioconductor
Changes in version 1.55.2
NEW FEATURES
Added accessor function to access pwm, ic and consensus
Added possibility to specify colors (by setting fill)
Added support for RNA logos
BUG FIXES
class
statements with is(..., "class")
Changes in version 1.27.1
Changes in version 1.19.2
Improvements
Transfer package maintainership.
Changes in version 1.19.1
Bug Fixes
Improvements
Changes in version 1.3.18
Make the package functions process-safe
Changes in version 1.3.8
Support complex
Support pairlist
Use memcpy to copy the data when possible
Changes in version 1.3.7
change the parameters of is.shared function
mustWork = FALSE
by default, no error will be given
when sharing a nonsharable object
Support environment object
Changes in version 1.3.6
Support S4 object
new dispatching method(signiture “ANY”) for share, unshare and is.shared functions
Changes in version 1.48
NEW FEATURES
countFastq()
counts the number of records,
nucleotides, and quality scores in one or several fastq files. Changes in version 1.2.4 (2020-08-14)
Supported defining gene set database from score matrix by setting higher, lower, as well as padj cutoffs for gCMAP and Fisher GESS methods
Changes in version 1.2.2 (2020-07-11)
Supported converting gmt file to HDF5 file (01 matrix) as gene set reference database for gCMAP and Fisher GESS methods
Changes in version 0.99.5
in the clustering, considered when the size of cluster is only 1.
add partition_by_kmeanspp()
.
col
can be set as a vector of colors.
Changes in version 0.99.4
support more ontologies.
support to calculate similarity matrix by gene overlap.
node partition fun changed to pam
Changes in version 1.12.0
Added the rowSubset() function as a standard location for a row subset.
Added colPairs() and rowPairs() to store pairwise information (e.g., for graphs).
Added method specifications for S4Vectors compatibility.
Changes in version 2.0.0 (2020-10-16)
Added quality control (empty droplet detection, doublet detection, etc) functionality
Ability to import data from varying preprocessing tools
Ability to export SingleCellExperiment object as varying file types (flat file, Python anndata)
Added functions for visualization of data
New CellViewer functionality in UI
Improvements to differential expression, now includes DESeq2, limma, ANOVA
Incorporates Seurat workflow
Changes in version 1.4.0
Migrated all of the dataset getter functions to the celldex package.
Streamlined the vignette to point to the book at <URL: http://bioconductor.org/books/devel/SingleRBook/>.
Added a restrict= argument to trainSingleR() and SingleR() to easily restrict to a subset of features.
Deprecated the method= argument in SingleR().
Protect against accidental data.frames in ref= or test= in all functions.
Changes in version 1.5.25
Bug fix: use ‘geom_point2’ instead of ‘geom_tippoint’ to avoid error.
Changes in version 1.5.24
Add sequence type option for for DNA and amino acid.
Deprecate ‘multiFixationSites’ function.
Use ‘y’ argument as mutation label option in ‘plot.sitePath’ function.
Finer lineage resolving method used in ‘lineagePath’ function.
Changes in version 1.5.23
Create ‘groupTips’ functions to replace ‘as.list’ functions for ‘fixationSites’ and ‘fixationPath’ object.
Create ‘sitesMinEntropy’ function to output raw result of entropy minimization.
Create ‘parallelSites’ function and other functions for its return object such as ‘plotSingleSite’ and ‘as.data.frame’
Changes in version 1.5.22
Fix missing newline when printing ‘phyMSAmatched’ object.
Create ‘as.list.fixationSites’ for retrieving grouped tips.
Remove ‘tipname’ option in ‘as.data.frame.fixationSites’.
Changes in version 1.5.21
Fix wrong group name in some corner cases.
Use ‘ggtree’ for ‘plotSingleSite’.
Changes in version 1.5.20
Further fix the merging issue in ‘fixationSites’.
Changes in version 1.5.19
Speed up ‘SNPsites’.
Changes in version 1.5.18
Bifurcation check for the phylogenetic tree and force bifurcation.
Fix path merging issue in ‘fixationSites’.
Changes in version 1.5.17
Import ‘aes’ and ‘theme’ from ‘ggplot2’.
Changes in version 1.5.16
Allow turning off mutation label for ‘plot.fixationSites’ while legend of cluster name becomes compulsory.
Import ‘scale_color_manual’ from ‘ggplot2’.
Update vignette.
Changes in version 1.5.15
Bug fix: NA in cluster name.
Changes in version 1.5.14
Add ‘as.treedata’ function for ‘fixationSites’.
Changes in version 1.5.13
Hierarchical naming of the clusters.
Changes in version 1.5.12
Establish ‘phyMSAmatched’ S3 class for better encapsulation.
Changes in version 1.5.11
Deprecate ‘multiFixationSites’ function.
Changes in version 1.5.8
Wrap mutations text in ‘plot.fixationSites’.
Remove ‘color’ argument for ‘plot.fixationSites’ as the number of groups is usually unknown.
Changes in version 1.5.7
Left padding with 0 for the cluster name.
Add mutation label when plot ‘fixationSites’.
Add ‘as.data.frame’ function for ‘fixationSites’.
Changes in version 1.5.6
Add ‘sitewiseClusters’ function and plot function for its visualization.
Changes in version 1.5.5
Add ‘plotMutSites’ function to visualize mutations of each tree tip.
Changes in version 1.5.4
Use ‘ggtree’ for ‘plot.lineagePath’.
More informative plot for ‘sneakPeek’ and add ‘lineagePath’ function for its return.
Changes in version 1.5.3
Add ‘as.phylo.fixationSites’ function that represent site fixations as simplified phylgenetic tree.
Changes in version 1.5.2
Add ‘minEffectiveSize’ in ‘plot.fixationSites’ for filtering small sized tip clusters.
Changes in version 1.5.1
Add ‘plot.fixationSites’ function.
Changes in version 1.4.1
Fix: broken link in the DESCRIPTION.
Changes in version 0.99.0 (2020-07-17)
Changes in version 1.24.0
snpgdsIBS
help file Changes in version 1.0.5 (2020-05-17)
Fix links in documentation to get rid of WARNINGS
Changes in version 1.0.4 (2020-05-17)
Fix bugs in colTabulates
Update documentation to avoid warnings in build on Windows
Changes in version 1.0.3 (2020-05-17)
Fix bug in colAnys and colAlls if value = TRUE
Changes in version 1.0.2 (2020-05-10)
Fix bug in colMaxs, colMins related to missing values
Changes in version 1.0.1 (2020-05-08)
Fix bugs in colMaxs, colMins, colAnys
Fix bug in colLogSumExps
Changes in version 2.0.0
Migration from Travis-CI to Github Actions.
Major refactoring.
Changes in version 0.99.0 (2020-10-02)
Changes in version 0.99.0 (2020-09-21)
Changes in version 0.99
Changes in 0.99.11
Changes in 0.99.10
Changes in 0.99.9
Changes in 0.99.8
Changes in 0.99.7
Changes in 0.99.6
Changes in 0.99.5
Changes in 0.99.4
Changes in 0.99.3
Changes in 0.99.2
Changes in 0.99.0
Changes in version 1.14.0 (2020-10-28)
Add the splatPop simulation. This is a extension to the splat simulation contributed by Christina Azodi and Davis McCarthy that adds population effects. It allows you to specify relatedness between individuals and generate cell-type specific eQTL effects.
Add a batch.rmEffect parameter to the Splat simulation. This allows generation of a paired simulation without any batch effects.
Add a new minimiseSCE function which can be used to remove unneeded information from simulation output (or any SingleCellExperiment)
All simulations now return sparse assay matrices by default when they would be smaller than the equivalent dense matrix. This is controlled by a new sparsify argument.
Users will now be automatically prompted to install packages if they try to use a simulation for which the suggested dependencies are not available
Changes in version 1.17.1 (2020-07-18)
Fixed bug. Limit for counter of inner loop in function splinePlot corrected
Signigicant changes o Log output to console in function splinePlot o package NEWS file added
Changes in version 0.99.0
Changes in version 2.0
NEW FEATURES
New GUI o Mouse Hover for help information o .log file
New Signal correction o Combat for QC-free Signal correction o QC-RFSC methods for metabolomics and proteomics data
New feature slection o Random Forest and the Permutation based variable importance measures o new MDSplot for Random Forest o P-value based importance plot
New data preprocessing o PQN/SUM/none normalization o center/none Scaling method
Changes in version 1.19.1
To fixed bugs for coCV function
Changes in version 1.1.2
improved ‘show’ output for objects
allow ANY for entities
Changes in version 1.1.1
added citations slot to struct classes
added corresponding citations method
added method to get/set seq_in slot
as.SummarizedExepriment now works correctly
using seq_in now works for sequences with more than 2 steps
Changes in version 1.1.2
Documentation updates
Bug fixes
Changes in version 1.0.1
Fix HCA bug
Changes in version 1.20.0
SIGNIFICANT USER-VISIBLE CHANGES
SummarizedExperiment now depends on the MatrixGenerics package.
DelayedArray was moved from Depends to Imports.
DEPRECATED AND DEFUNCT
BUG FIXES
Avoid triggering copies of the assays in assays() getter.
Fix long-standing bug in dim() method for Assays objects.
Fix assays(x) <- SimpleList(). Before that fix this operation was turning SummarizedExperiment object (or derivative) ‘x’ into an invalid object.
Changes in version 1.19.3
UPDATE
Add link to website
Changes in version 1.19.2
BUG FIXES
remove grid from Description
Changes in version 1.19.1
NEW FEATURES
update
update documentation to roxygen2 (many thanks to Ashton Trey Belew (abelew) for starting this and doing most of the work) (IS#1, PR#2, PR#3)
Some parameters were renamed to omit having a dot. E.g. rm.decoy is now called rm_decoy. If you want the previous names use SWATH2stats up to version 1.19.0
Changes in version 1.19.0
NEW FEATURES
Changes in version 0.99.35 (2020-05-15)
Proper formatting of the NEWS file
Changes in version 0.99.33 (2020-04-27)
Submitted to Bioconductor
Changes in version 1.46.0
NEW FEATURES
New function ri_data_extract
to extract peaks from RI files. It
works
similar to FindAllPeaks
but uses different (simpler) input
parameters,
comparable to ncdf4_data_extract.
New function ri_plot_peak
to plot peaks from RI files, built upon
ri_data_extract
. It can be used as an alternative to plotPeakRI
as it
has a simple interface.
New function ncdf4_plot_peak
. An alternative to function
plotPeakSimple
with a simple interface to plot peaks from NetCDF format 4. This
function
supersedes plotPeakSimple
.
BUG FIXES
Remove unneeded ICO file.
Man pages improvements. Mostly grammar and spelling changes.
SIGNIFICANT USER-VISIBLE CHANGES
The function peakPlotSimple
is considered deprecated, and its
use should be avoided. Use the function ncdf4_plot_peak
instead.
The parameter column
in many columns is now NULL
by default. To
change the column names use the global option TS_RI_columns
instead
Changes in version 1.29.1
Changes in version 1.10.0
New features
Minor changes and bug fixes
Changes in version 099.1
SIGNIFICANT USER-VISIBLE CHANGES
INTERNALS
depends now on ProtGenerics from which it uses ‘mz’
exchanged various print() with message()
Changes in version 0.99.0 (2020-09-15)
Changes in version 1.5.3
Small tweaks to better display weitrix_confect outputs.
Less digits when print()ed.
Changes in version 1.5.2
nest_confects now copes with NA p-values.
Changes in version 1.5.1
Fix limits calculation for confects_plot.
Changes in version 1.1.0
Include scripts for differential expression analysis and GSEA of toxico-genomic data (limma)
Changes in version 1.0.0
Abstracted some additional functions to CoreGx
Changes in version 0.1.2
Modified rankGeneDrugsPerturbation to fix a bad unit conversion which would return concentrations in the wrong unit
Changes in version 0.1.1
Bug Fix: Regenerated TGGATESsmall (sample dataset) to fix make a result in the vignette consistent with previous releases.
Changes in version 0.1.0
Improved package documentation
Changes in version 0.0.1
Changes in version 3.17.6
fix warnings due to unused argument of select(!!!syms(…)) statement during histogram generation for reference data
Changes in version 3.17.5
fix bugs and warnings in executable examples
Changes in version 3.17.4
fix errors in build report on Bioconductor
fix warnings due to conversion of non-numeric values during 2D-TPP import
fix warnings in ggplot command
upgrade deprecated dplyr functions
make syntax of testthat checks more consistent across files
Changes in version 3.17.2-3
Fixed bugs and warnings after update to dplyr v1.0.0.
Changes in version 3.17.1
Fixed bug in tpp2dCreateTPPTRreferenece upon user request (#10)
removed adding spline fit column from 2DTPP output table
fixed bug in tpp2dCreateTPPTRReference and made example in vignette work
removed leftover parameters in tpp2dCreateTPref function
final fix of tpp2dCreateTPPTRreference and call in vignette now works
Changes in version 3.17.0
New Bioconductor release candidate
Changes in version 1.5.5
new visualization options
volcanoplot: plot2dTppVolcano
heatmap of fold changes: plot2dTppFcHeatmap
Changes in version 1.4.1 (2020-06-20)
bug fix in moderated F statistic computation - old version is unneccessarily stringent
Changes in version 1.25.4
remove http_status from documentation.
add function to split the lollipop plot into multiLayers.
Changes in version 1.25.3
Fix the issue in AddArrowMark that grid changed the unit id.
Changes in version 1.25.2
Fix the issue if there is interrupt of the internet connection to generate vignette.
Changes in version 1.25.1
Provide more clearly warning or error message if the input is not sorted or contain NA values.
Changes in version 1.3.19 (2020-10-16)
conditions
branch into master
. Now the master
branch can
therefore handle multiple conditions. There is a new conditions
argument in fitGAM
to handle that, and a condition-specific
smoother will be fitted for each lineage. There is also a new test,
conditionTest
, which tests for DE between conditions within a
lineage. The way this is done under the hood is exactly like the
patternTest
. Changes in version 1.6.3
added limits argument for spectrum plot x-values to harmonize color scale of multiple spectrum plots
replaced Rcpp::RcppArmadillo::sample() with now fixed Rcpp::sample()
Changes in version 1.6.2
updated paper references
fixed minor formatting issues
incremented Roxygen2 version
Changes in version 1.0.0
SIGNIFICANT USER-VISIBLE CHANGES
NEW FEATURES
Changes in version 1.13.1
Changes in version 2.21.1
Changes in version 1.28.0
Added createClusterMST() to create a cluster-based MST from a variety of inputs, migrated from the scran package.
Added reportEdges() to report edge coordinates for plotting.
Added mapCellsToEdges() to map cells to the closest edge on the MST.
Added orderCells() to compute a pseudotemporal ordering from mapped cells.
Added quickPseudotime() to wrap MST construction and ordering into a single call.
Added testPseudotime() to test for DE genes along one or more paths through a MST.
Added the rowmean() utility to compute column means for row groupings.
Added perCellEntropy() to compute per-cell entropies across various matrix types.
Changes in version 1.8.0
Added ‘fromDb’ argument to addIds() to allow IDs to be added from the associated TxDb/EnsDb instead of the org package (which is used by default). Feature suggestion from Kristoffer Vitting-Seerup.
Added function retrieveCDNA() that will download or load a cached version of the transcript sequences used for quantification. Note that the returned sequences are not ordered or matched to the rows of the SummarizedExperiment object. Feature suggestion from Kristoffer Vitting-Seerup.
Added function addCDS() that will add CDS ranges for coding transcripts (and fills in original ranges for non-coding), as well as a ‘coding’ column as a logical indicator. Feature suggestion from Kristoffer Vitting-Seerup.
Added option that environmental variable TXIMETA_HUB_CACHE can be used to set tximeta’s cache location, to avoid prompting the user on the first run of tximeta().
tximeta() will now pull GENCODE TxDb from AnnotationHub when it is listed there (only Homo sapiens are at this point in time). Thanks to Leonardo Collado-Torres for the suggestion!
Now summarizeToGene() will add a column tx_ids, which is a CharacterList of the transcript IDs.
Changes in version 1.7.13
Added ‘fromDb’ argument to addIds() to allow IDs to be added from the associated TxDb/EnsDb instead of the org package (which is used by default). Feature suggestion from Kristoffer Vitting-Seerup.
Changes in version 1.7.12
Added function retrieveCDNA() that will download or load a cached version of the transcript sequences used for quantification. Note that the returned sequences are not ordered or matched to the rows of the SummarizedExperiment object. Feature suggestion from Kristoffer Vitting-Seerup.
Changes in version 1.7.11
Added function addCDS() that will add CDS ranges for coding transcripts (and fills in original ranges for non-coding), as well as a ‘coding’ column as a logical indicator. Feature suggestion from Kristoffer Vitting-Seerup.
Changes in version 1.7.10
Added option that environmental variable TXIMETA_HUB_CACHE can be used to set tximeta’s cache location, to avoid prompting the user on the first run of tximeta().
Changes in version 1.7.9
tximeta() will now pull GENCODE TxDb from AnnotationHub when it is listed there (only Homo sapiens are at this point in time). Thanks to Leonardo Collado-Torres for the suggestion!
Changes in version 1.7.6
Now summarizeToGene() will add a column tx_ids, which is a CharacterList of the transcript IDs.
Changes in version 1.7.1
Updated to Ensembl release 100, GENCODE 34/M25.
Changes in version 1.18.0
Changes in version 0.99.21
Improvements in vignette and documentation.
Changes in version 0.99.20
Avoid duplication of fragment end calculation in plotDifferential for DESeq2 results.
Changes in version 0.99.19
Minor documentation changes to pass Bioconductor checks.
Changes in version 0.99.18
Fix DESeq2 example.
Reduce size of installed example tsv.gz count files.
Changes in version 0.99.17
Re-run example datasets and use again links from figshare.
Changes in version 0.99.16
IMPORTANT
contactsUMI4C()
again to
generate
updated .tsv.gz files.UPDATES
Improved grouping arguments for UMI-4C objects: now creates a new
UMI-4C
object that can be accessed using groupsUMI4C(umi4c)$condition
.
This allows
retaining replicate information in the main UMI4C object while
allowing
plotting grouped trends stored in groupsUMI4C()
.
Added new statistical test using DESeq2:
differentialNbinomWaldTestUMI4C()
.
Changes in version 0.99.15
Fixed duplicated read number in read id (.singlePrepUMI4C) (see issue #5).
Changed example download urls to gattaca server.
Changes in version 0.99.14
Fixed bug where adaptive smoothed trend was normalized twice (see issue #4).
Changes in version 0.99.11
Uploaded example datasets urls in downloadUMI4CexampleData()
to a
more
stable and permanent location (figshare.com).
Changes in version 0.99.10
Avoid running long and redundant examples, already tested in the vignette to avoid TIMEOUT build error.
Changes in version 0.99.9
Add data object ex_ciita_umi4c
to use in examples and reduce check
running
times.
Changes in version 0.99.8
Update package vignette to clarify the origin of the different sample files used to exemplify a workflow using the UMI4Cats package.
Changes in version 0.99.7
Added unit tests using testthat
.
Use BiocFileCache to download sample files.
Use tempdir() for demo purposes both in vignette and examples.
Added inst\scripts to describe how the sample data was generated.
Other minor changes to comply with Bioconductor review (see https://github.com/Pasquali-lab/UMI4Cats/issues/2#issue-637249954)
Changes in version 0.99.6
Delete downloaded and intermediate folders when building vignette.
Added UMI4Cats_index
to .Rbuildignore to prevent ERRORs and
WARNINGs in BioCCheck.
Changes in version 0.99.5
Increased speed of getViewpointCoordinates()
by allowing
pre-selection
of viewpoint chromosome using sel_seqname
argument.
Added reduced fastq files in extdata and allow downloading of reduced bowtie index to increase vignette building speed.
Changes in version 0.99.4
Added .Rproj
files to .gitignore
Changes in version 0.99.3
Changed example in vignette and manuals to CIITA.
Added viewpoint name in plotTrend()
.
Improved multi-panel plotting of plotUMI4C()
.
Changes in version 0.99.2
Allow ref_umi4c
to be used as reference for plotting colors,
domainogram
and differential analysis (not only for normalization).
Fixed error when using sampleID
as grouping
variable in
makeUMI4C()
.
Fixed bug in results()
when fomat=data.frame
and ordered=TRUE
.
Improved visualization of differential regions reconverting Inf
and
-Inf
to maximum and minimum (respectively) odd’s ratio values.
Add more functionality details in the Analyzing UMI-4C data with
UMI4Cats
vignette.
Changes in version 0.99.1
Fixed error in function createGeneAnnotation
and plotGenes
that
occurs
when there are no genes in the region or a gene has multiple
identifiers.
Fixed duplicated generics definition for SummarizedExperiment
objects to
avoid error when reloading the package.
Fixed error when bait_exclusion
is set to 0.
Added possibility to specify the sample to use as reference for
normalization
(ref_umi4c
argument in makeUMI4C
).
Now the grouping
variable in makeUMI4C()
is used more upstream in
the
analysis. For using different grouping variables, user must create
different
UMI4C
objects.
Fixed bug where sometimes bait coordinates in the output tsv file are
NA
.
statsUMI4C
now also outputs a stats summary table in
wk_dir/logs/stats_summary.txt
.
Improve function documentation.
Improve pkgdown UMI4Cats site.
Rewrite and improve the Analyzing UMI-4C data with UMI4Cats
vignette.
Changes in version 0.99.0
First public release of UMI4Cats.
Added a NEWS.md
file to track changes to the package.
Changes in version 0.0.0.9000
setup
Changes in version 1.8.0
NEW FEATURES
scan_sequences()/enrich_motifs() can now be used to scan/enrich for gapped motifs. A new section has been added to the SequenceSearches.Rmd vignette.
scan_sequences(…, use.gaps), enrich_motifs(…, use.gaps): ignore motif gap information.
read_meme(), write_meme(): now fully support custom alphabets.
prob_match(), prob_match_bkg(): calculate the probability of a motif match based on background frequencies of the motif object or provided values, respectively.
enrich_motifs(), get_matches(), get_scores(), motif_pvalue(), motif_score(), scan_sequences(), score_match(): new allow.nonfinite parameter, allowing for the functions to work even if non-finite values are present in the motif PWM.
read_matrix(…, comment): allows for comments to be ignored in motif files.
write_matrix(…, digits): control the number of digits to use for writing motif positions.
New mask_seqs() utility function: inject hard masks into sequences.
scan_sequences(…, warn.NA), enrich_motifs(…, warn.NA): new option which can disable warnings from non-standard letters being detected in the input sequences.
get_bkg(…, window, window.size, window.overlap): new options for calculating sequence background in windows.
get_bkg(…, merge.res): new option to return background information for individual sequences.
scan_sequences(…, calc.pvals): new option to calculate P-values for sequence hits. This is merely automating using the results from scan_sequences() to calculate P-values manually with motif_pvalue().
view_motifs(…, show.positions, show.positions.once, show.names): new options for customizing the look of plotted motifs.
MINOR CHANGES
read_matrix(…, positions): added partial argument matching.
create_sequences(), shuffle_sequences(), motif_pvalue(): the c++ random engine has been changed from std::default_random_engine to std::mt19937. This should allow for the same rng.seed value to result in the same output regardless of OS.
score_match() has been vectorized (alongside new prob_match() function).
The ape and ggtree packages are now no longer imported and must be installed seperately in order to use motif_tree().
The processx package is no longer imported and must be installed seperately in order to use run_meme().
The pseudocount slot is now shown when universalmotif class objects are printed.
get_bkg(): the list.out and as.prob options have been disabled. To simplify the function, the only possible output (exception: if to.meme is not NULL) is a DataFrame showing both counts and probabilities.
Changed the default look of motifs plotted by view_motifs().
General documentation cleanup.
BUG FIXES
Changing motif backgrounds with [<-
will now make sure to set
correct
vector names.
get_bkg() will now correctly ignore non-standard letters and letters missing from the provided alphabet during counting.
Changes in version 1.6.4
BUG FIXES
cbind(): do not ignore the pseudocount slot.
Fixed typo in IntroductionToSequenceMotifs.Rmd.
Fixed U() function in IntroductionToSequenceMotifs.Rmd, no longer returns NA values if 0s are present.
read_cisbp(): no parsing errors for motifs with missing/partial header info.
Changes in version 1.6.3
BUG FIXES
scan_sequences(): commented out WIP code for scanning gapped motifs.
Changes in version 1.6.2
BUG FIXES
motif_tree(): ‘daylight’ layout is no longer disabled.
Changes in version 1.6.1
BUG FIXES
summarise_motif(): properly retrieves altname slot. Contribution from Spencer Nystrom (https://github.com/bjmt/universalmotif/pull/9).
read_meme(): for LIKE type alphabets, make sure PROTEIN-LIKE is understood as being AA.
Changes in version 1.19.20
fix bug discovered when the number of features is less than the number of chunks in iterBatch()
Changes in version 1.19.19
simple bug fixes to pass R CMD check
Changes in version 1.19.18
simplify calcVarPart for lm and lmer. Add compatibility for glm
Simplify checkModelStatus.merMod to allow formula (A|B) where A is continuous
remove unused “adjust” arguments for clarity
Changes in version 1.19.17
add get_prediction() for results of lm()
improve documentation of get_prediction()
Changes in version 1.19.16
in canCorPairs() change statistic used to summarize CCA to Cramer’s V. The difference is very subtle, but is now based on first principles.
in dream, check that data is a data.frame
dream() defaults to computeResiduals=TRUE for compatability with zenith
Changes in version 1.19.14
fix issue with residuals() where examples fail
Changes in version 1.19.13
fix issue exporting eBayes, topTable, etc
Changes in version 1.19.12
Improve documentation for contrasts in dream.Rmd
check that contrasts sum to zero in plotContrasts.
Changes in version 1.19.11
https://github.com/GabrielHoffman/variancePartition/issues/17
Changes in version 1.19.10
in voomWithDreamWeights() fix issue with returning design matrix
https://github.com/GabrielHoffman/variancePartition/issues/15
Changes in version 1.19.7
Round numbers in plotContrasts()
fix issues with strings are passed to formula arguments
Changes in version 1.19.6
New gives meaning full error message for dream(), etc when variable is not found in data.
Changes in version 1.19.5
Better error catching when running fitVarPartModel() with fxn that fails
the following code now can be run in parallel fitList = fitVarPartModel( Y, ~ (1|Batch), data, fxn = function(fit){ B = variancePartition::get_prediction(fit, ~(1|Batch)) fit@resp$y - B }, BPPARAM=SnowParam(3))
Changes in version 1.19.4
Update vignette #3, and update documentation of REML argument
Changes in version 1.19.3
add new FAQ.Rmd
Changes in version 1.19.2
canCorPairs() now returns NA correlation when two variables have no overlapping observed values
plotCorrMatrix() now handles NA correlation values
Changes in version 1.19.1
Bump to next Bioconductor version
Changes in version 1.18.3
Improve documentation
move location of eBayesFMT code
Changes in version 1.18.2
Clean up some code and add documentation
document ebayesFMT
Changes in version 1.18.1
Clean up some code and add documentation
Changes in version 1.36.0
NEW FEATURES
Changes in version 0.99.9
Converted various functions to S4 generics for easier use with SingleCellExperiment objects.
Changes in version 0.99.8
Trigger new build to repeat ExperimentHub download.
Changes in version 0.99.7
Delete empty line to force cache update. See https://github.com/rubocop-hq/rubocop/pull/4342#issuecomment-305449759.
Changes in version 0.99.6
Set autoscale=FALSE in the call to scvelo function velocity_embedding to avoid issue related to Qt and plotting.
Changes in version 0.99.5
Trigger new build to check if Windows issue resolved itself.
Changes in version 0.99.4
Trigger new build to check whether TIMEOUT issue on Windows is reproducible.
Changes in version 0.99.3
Explicitly declare all Conda dependencies for scvelo.
Changes in version 0.99.2
Add hexsticker.
Changes in version 0.99.1
Remove .Rproj file from git repository.
Changes in version 0.99.0
First submission to Bioconductor.
Changes in version 1.0.0
Changes in version 1.3
print graph with orca
Ensembl2GO() biomart update
show_heatmap() upgrade
upset print update
merge_enrich_terms upgrade pvalue cutoff
merge_enrich_terms globale upgrade
GOterms_heatmap remove row side colors text and correct showIC column
vignettes update
annotate() update for uniprot
fgsea support
Changes in version 0.5.0 (2020-05-25)
IMPORTANT:
Created plotProfile function
MINOR:
Changed color scale to scico package, roma scale
Changes in version 0.4.2 (2020-05-10)
IMPORTANT:
Added plot theming
MINOR:
Changes in version 2.23.0
Changes in version 1.1.10
Fix bug with weitrix_confects due to [[ ]] <- NULL deleting elements from a list instead of storing NULL in the list.
Changes in version 1.1.9
Try to get rid of an odd new build error about stack usage by using serial processing in vignettes.
Changes in version 1.1.8
Use geom_bin2d in weitrix_calplot scatterplots.
Changes in version 1.1.7
Add mu_min, mu_max arguments to weitrix_calibrate_all.
Changes in version 1.1.6
Add SLAM-Seq vignette.
Changes in version 1.1.5
well_knotted_spline for natural splines with good choice of knots.
Changes in version 1.1.4
weitrix_calplot now shows mean trend and mean +/- standard deviation trend.
Changes in version 1.1.3
Add weitrix_rms_confects to find rows with confidently excessive variation.
Changes in version 1.1.2
weitrix_calplot now uses sqrt(weight)*residual on y axis.
Changes in version 1.1.1
Changes in version 0.99.13
Revised all documentation of functions
Changes in version 0.99.12
added an infobox for plate dimensions compatibility with the number of samples
Changes in version 0.99.11
updated Vignette and Help page about toy dataset (CSV section)
Changes in version 0.99.10
corrected the Parameters section in the Vignette
Changes in version 0.99.9 (2020-06-18)
added preview of CSV file when importing in the UI
Changes in version 0.99.8 (2020-06-11)
Updated images and text in the tutorial vignette.
Changes in version 0.99.7 (2020-06-05)
Created a new module for the integration of markdown files in the shiny application.
Changes in version 0.99.6 (2020-06-02)
Updated the README file and the tutorial vignette explaining how to use WPM using command line.
Changes in version 0.99.5 (2020-06-02)
Added unit tests for import functions
Changes in version 0.99.4 (2020-05-28)
Fix the TIMEOUT error during R CMD CHECK
Changes in version 0.99.3 (2020-05-28)
Added Rd examples for convertVector2Df and drawMap functions
Changes in version 0.99.2
Changes in version 3.11.8
Disable parallel processing in vignettes.
Changes in version 3.11.7
More efficient splitting data per file especially for larger data sets.
Disable parallel processing in examples.
Changes in version 3.11.6
Add FilterIntensityParam
to filter chromatographic peaks on
intensity
(issue #502).
Add estimatePrecursorIntensity
function to determine the precursor
intensity
for MS2 spectra from the neighboring MS1 spectra.
Changes in version 3.11.4
Change from Spectra
and Chromatograms
to MSpectra
and
MChromatograms
from MSnbase version >= 2.15.3.
Changes in version 3.11.3
reconstructChromPeakSpectra
: report also polarity and
precusorIntensity
.
reconstructChromPeakSpectra
: ensure a retention time is reported
for
reconstructed MS2 spectra (issue #485).
Change default for expandRt
to 0
in
reconstructChromPeakSpectra
.
Fix error in refineChromPeaks,MergeNeighboringPeaksParam
if no
peaks found
to be merged.
Changes in version 3.11.2
Add fillChromPeaks,ChromPeakAreaParam
to base the area from which
missing
peak data should be filled-in on the actually detected
chromatographic peaks
of a feature.
Potential fix for issue #481: function should no longer throw an error because retention times are of length 0.
More efficient splitting of processing which should increase the speed of the findChromPeaks, refineChromPeaks, reconstructChromPeakSpectra and chromPeakSpectra calls.
Changes in version 3.11.1
Fix issue #471: conversion from XCMSnExp
to xcmsSet
looses
phenodata
(thanks to Andris Jankevics for reporting and providing a solution).
Add normalize
method for Chromatogram
and Chromatograms
objects.
featureChromatograms
gets new parameter n
and value
to extract
EICs
only from the top n samples with highest intensities.
filterFile
gets new parameter keepFeatures
to support retaining
correspondence results even if a data set is filtered by file.
Export the virtual Param
class.
Add filterColumnsIntensityAbove method for Chromatograms object that allows to select columns (samples) of an Chromatograms object for which intensities of its chromatographic data are higher than a threshold.
Add removeIntensity method for Chromatogram, Chromatograms, XChromatogram and XChromatograms objects allowing to remove intensities based on different criteria.
Add correlate method for Chromatograms allowing to correlate multiple chromatograms with each other.
Changes in version 1.0.0
Accepted into Bioconductor for Release 3.12
zellkonverter provides methods to convert between Python AnnData objects and SingleCellExperiment objects. These are primarily intended for use by downstream Bioconductor packages that wrap Python methods for single-cell data analysis. It also includes functions to read and write H5AD files used for saving AnnData objects to disk.
Changes in version 1.11.6 (2020-07-18)
Fixed a bug in the initialization of beta_j.
Fixed a bug in zinbsurf.
Changed zinbwave default to K=2
.
Fix bug in the initialization of W.
Changes in version 1.6.0
Changes in version 0.99.4 (2020-09-02)
Add mouse atlas
Changes in version 0.99.0 (2020-07-02)
Cleanup for bioc
Changes in version 1.12.0
Bug fixes and minor improvements
Output dataset options as table when dry.run is enabled in the main function.
Check for RaggedExperiment dependency when loading data that uses the data representation (@vjcitn, #39)
Changes in version 1.3
Changes in version 1.3.2
Changes in version 1.3.1
Changes in version 1.1.2 (2020-10-08)
Changed TF census from TFclass to the more recent version from Lambert et al.. Information of mode of regulation for each TF (activator, supressor, dual) is still taken from Garcia-Alonso et al..
Updated deprecated gene symbols to their latest version with the limma package (version 3.44.3).
Shifted viper package from suggest to depends in the DESCRIPTION file.
Added a further argument specifially for run_viper().Seurat to select a specific assay name to extract the normalized gene expression values from.
Changes in version 1.1.1 (2020-09-02)
Export df2regulon function
Improved documentation (added gh page URL to DESCRIPTION)
Changes in version 1.0.1 (2020-08-13)
Improved package documentation
Updated link to 10x genomics data set in single-cell vignette
Fixed tests related to Seurat and SCE class
Changes in version 2.17
USER VISIBLE CHANGES
Changes in version 0.99.2 (2020-09-20)
(0.99.2) Added PMCID and PMID in reference to original study
(0.99.2) Updated citation to include full reference
(0.99.2) Minor improvements in readability of R code
Changes in version 0.99.1 (2020-07-24)
(0.99.1) Simplified vignette Installation code
(0.99.1) Updated vignette typical-filter code chunk to evaluate as R code
Changes in version 0.99.0 (2020-07-14)
(0.99.0) Passed R CMD check and R CMD BiocCheck without errors or warnings
(0.99.0) Submitted to Bioconductor
Changes in version 0.1.0 (2020-07-03)
(0.1.0) Begin building FieldEffectCrc package
Changes in version 1.0.0
Changes in version 1.27.1
Changes in version 1.8.0
added funtionality for include survey weights via survey::svyglm
fixed bug whereby, in ceratin situations, an incorrect number of blocks would be calculated
Changes in version 1.27.1
Changes in version 1.0.0
Changes in version 2.4.0
Added the Zilionis lung dataset (Jens Preussner).
Added the Hermann spermatogenesis dataset (Charlotte Soneson).
Added the Mair and Kotliarov PBMC datasets (Stephany Orjuela).
Added the Stoeckius cell hashing dataset.
Added the Wu kidney snRNA-seq dataset.
Added the Hu cortex snRNA-seq dataset.
Added spike-in concentrations to the altExp rowData for various datasets (Alan O’Callaghan).
Changes in version 1.2.1 (2020-08-14)
Changes in version 1.2.0
New features
CITEseq function, vignette, and ‘cord_blood’ data available (@drighelli, #18)
Include seqFISH function, vignette, and ‘mouse_visual_cortex’ data (v1 and v2 from @drighelli, #14)
New ‘mouse_gastrulation’ dataset released (version “2.0.0”).
Use version argument to indicate the mouse_gastrulation data version
The data includes all cells not only the ones that passed the QC of all three ‘omics (thanks @rargelaguet, @ajabadi).
Bug fixes and minor improvements
Caching mechanism uses tools::R_user_dir and not rappdirs.
Improved display of available data using ExperimentHub metadata.
Improved documentation explaining versioning differences.
Contribution guidelines available at https://github.com/waldronlab/SingleCellMultiModal/wiki/Contributing-Guidelines
Default version argument in scNMT function now set to “2.0.0” (version “1.0.0” still available)
Changes in version 1.1.5
NEW FEATURES
fetch_data() takes the data from sce object and creates a VisiumExperiment object containing these data. VisiumExperiment object can be obtained with fetch_data(“ve”).
Changes in version 1.1.4
NEW FEATURES
Changes in version 0.99.0 (2020-05-15)
Changes in version 0.99.6
Renamed Vignette to TMExplorer (“tutorial” was too generic)
More man page updates
Changes in version 0.99.5
Updated man pages and cleaned up some code.
Changes in version 0.99.3 (2020-07-03)
Fixed a bug when downloading data on Windows
Changes in version 0.99.2 (2020-07-03)
Fixed missing cell type labels in some datasets
Changes in version 0.99.1 (2020-06-25)
Now uses SingleCellExperiment objects
Changes in version 0.99.0 (2020-06-22)
Submitted to Bioconductor
Changes in version 1.0.1
Fifty Six software packages were removed from this release (after being deprecated in Bioc 3.11): affypdnn, AnalysisPageServer, anamiR, BayesPeak, bgafun, biosvd, birta, CALIB, CAMTHC, cellGrowth, chroGPS, cobindR, CTDquerier, CVE, DChIPRep, DEDS, DupChecker, FEM, gCMAP, gCMAPWeb, geecc, Genominator, IdMappingAnalysis, IdMappingRetrieval, IPPD, kimod, LMGene, lol, LVSmiRNA, M3D, manta, MaxContrastProjection, MCRestimate, MergeMaid, mitoODE, MoPS, motifRG, MTseeker, nem, PAPi, pcaGoPromoter, pint, plw, PowerExplorer, proteoQC, QUALIFIER, readat, RefNet, RIPSeeker, SANTA, scfind, splicegear, sRAP, triform, Vega, waveTiling
Sixty eight software are deprecated in this release and will be removed in Bioc 3.13: adaptest, ArrayTV, BioSeqClass, CGEN, CHARGE, chimera, CNVtools, CorMut, DESeq, explorase, flowFit, flowSpy, flowType, flowVS, focalCall, FourCSeq, FunciSNP, GeneticsDesign, GenRank, GGBase, GGtools, GOFunction, gQTLBase, gQTLstats, hicrep, ImpulseDE, ImpulseDE2, joda, JunctionSeq, LINC, Logolas, mcaGUI, metaArray, metaseqR, methVisual, methyvim, Mirsynergy, MmPalateMiRNA, MOFA (Please see MOFA2), MotIV, NarrowPeaks, netbenchmark, netReg, OGSA, OmicsMarkeR, pathprint, PathwaySplice, PGA, PGSEA, plrs, prada, Prize, Rariant, reb, Roleswitch, rTANDEM, sampleClassifier, sapFinder, scsR, shinyTANDEM, sigaR, signet, simpleaffy, spotSegmentation, Starr, SVAPLSseq, TxRegInfra, xps
Two experimental data packages were removed this release (after being deprecated in BioC 3.11): MTseekerData, RIPSeekerData
Sixteen experimental data packages are deprecated in this release and will be removed in Bioc 3.13: flowFitExampleData, FunciSNP.data, geuvPack, geuvStore2, GGdata, methyvimData, mitoODEdata, Mulder2012, pathprintGEOData, pcaGoPromoter.Hs.hg19, pcaGoPromoter.Mm.mm9, pcaGoPromoter.Rn.rn4, RNAinteractMAPK, sampleClassifierData, waveTilingData, yriMulti
Nine annotation packages were supposed to be removed this release, however we decided to give an extra cycle for maintainers to adapt and will be removed in 3.13: hom.At.inp.db, hom.Ce.inp.db, hom.Dm.inp.db, hom.Dr.inp.db, hom.Hs.inp.db, hom.Mm.inp.db, hom.Rn.inp.db, hom.Sc.inp.db, KEGG.db.
Five annotation packages are deprecated in this release and will be removed in Bioc 3.13: MeSH.Eco.55989.eg.db, MeSH.Eco.ED1a.eg.db, MeSH.Eco.IAI39.eg.db, MeSH.Eco.UMN026.eg.db, MeSH.Eqc.eg.db (renamed to MeSH.Eca.eg.db)
No workflow packages were removed in this release.
No workflow packages were deprecated in this release.