Registration and Call for Abstracts Open for Bioc2024

May 1, 2018


We are pleased to announce Bioconductor 3.7, consisting of 1560 software packages, 342 experiment data packages, 919 annotation packages, and 21 workflows.

There are 98 new software packages, 16 new data experiment packages, 2 new workflows, and many updates and improvements to existing packages; Bioconductor 3.7 is compatible with R 3.5.0, and is supported on Linux, 32- and 64-bit Windows, and Mac OS X. This release will include an updated Bioconductor Amazon Machine Image and Docker containers.

Visit for details and downloads.


Getting Started with Bioconductor 3.7

To update to or install Bioconductor 3.7:

  1. Install R >=3.5.0. Bioconductor 3.7 has been designed expressly for this version of R.

  2. Follow the instructions at

New Software Packages

There are 98 new software packages in this release of Bioconductor.

  • adaptest Data-adaptive test statistics represent a general methodology for performing multiple hypothesis testing on effects sizes while maintaining honest statistical inference when operating in high-dimensional settings. The utilities provided here extend the use of this general methodology to many common data analytic challenges that arise in modern computational and genomic biology.

  • ASICS With a set of pure metabolite reference spectra, ASICS quantifies concentration of metabolites in a complex spectrum. The identification of metabolites is performed by fitting a mixture model to the spectra of the library with a sparse penalty. The method and its statistical properties are described in Tardivel et al. (2017) <doi:10.1007/s11306-017-1244-5>.

  • bcSeq This Rcpp-based package implements a highly efficient data structure and algorithm for performing alignment of short reads from CRISPR or shRNA screens to reference barcode library. Sequencing error are considered and matching qualities are evaluated based on Phred scores. A Bayes’ classifier is employed to predict the originating barcode of a read. The package supports provision of user-defined probability models for evaluating matching qualities. The package also supports multi-threading.

  • BEARscc BEARscc is a noise estimation and injection tool that is designed to assess putative single-cell RNA-seq clusters in the context of experimental noise estimated by ERCC spike-in controls.

  • BiFET BiFET identifies TFs whose footprints are over-represented in target regions compared to background regions after correcting for the bias arising from the imbalance in read counts and GC contents between the target and background regions. For a given TF k, BiFET tests the null hypothesis that the target regions have the same probability of having footprints for the TF k as the background regions while correcting for the read count and GC content bias. For this, we use the number of target regions with footprints for TF k, t_k as a test statistic and calculate the p-value as the probability of observing t_k or more target regions with footprints under the null hypothesis.

  • BiocOncoTK Provide a central interface to various tools for genome-scale analysis of cancer studies.

  • BioNetStat A package to perform differential network analysis, differential node analysis (differential coexpression analysis), network and metabolic pathways view.

  • CAGEfightR CAGE is a widely used high throughput assay for measuring transcription start site (TSS) activity. CAGEfightR is an R/Bioconductor package for performing a wide range of common CAGE data analysis tasks. Core functionality includes: import of CAGE TSSs (CTSSs), tag (or unidirectional) clustering for TSS identification, bidirectional clustering for enhancer identification, annotation with transcript and gene models, calculation of TSS shapes and quantification of CAGE expression as expression matrices.

  • ccfindR A collection of tools for cancer single cell RNA-seq analysis. Cell clustering and feature gene selection analysis employ maximum likelihood and Bayesian non-negative matrix factorization algorithm. Input data set consists of RNA count matrix, gene, and cell bar code annotations. Analysis outputs are factor matrices for multiple ranks, quality measures (maximum likelihood) or evidence (Bayesian) with respect to rank. The package includes utilities for downstream analyses, including meta-gene identification, visualization, and construction of rank-based trees for cell clusters.

  • CellScore The CellScore package contains functions to evaluate the cell identity of a test sample, given a cell transition defined with a starting (donor) cell type and a desired target cell type. The evaluation is based upon a scoring system, which uses a set of standard samples of known cell types, as the reference set. The functions have been carried out on a large set of microarray data from one platform (Affymetrix Human Genome U133 Plus 2.0). In principle, the method could be applied to any expression dataset, provided that there are a sufficient number of standard samples and that the data are normalized.

  • CHARGE Identifies genomic duplications or deletions from gene expression data.

  • ChIC Quality control pipeline for ChIP-seq data using a comprehensive set of quality control metrics, including previously proposed metrics as well as novel ones, based on local characteristics of the enrichment profile. The framework allows assessing quality of samples with sharp or broad enrichment profiles, whereas previously proposed metrics were not taking this into account. CHIC provides a reference compendium of quality control metrics and trained machine learning models for scoring samples.

  • ChIPSeqSpike Chromatin Immuno-Precipitation followed by Sequencing (ChIP-Seq) is used to determine the binding sites of any protein of interest, such as transcription factors or histones with or without a specific modification, at a genome scale. The many steps of the protocol can introduce biases that make ChIP-Seq more qualitative than quantitative. For instance, it was shown that global histone modification differences are not caught by traditional downstream data normalization techniques. A case study reported no differences in histone H3 lysine-27 trimethyl (H3K27me3) upon Ezh2 inhibitor treatment. To tackle this problem, external spike-in control were used to keep track of technical biases between conditions. Exogenous DNA from a different non-closely related species was inserted during the protocol to infer scaling factors that enabled an accurate normalization, thus revealing the inhibitor effect. ChIPSeqSpike offers tools for ChIP-Seq spike-in normalization. Ready to use scaled bigwig files and scaling factors values are obtained as output. ChIPSeqSpike also provides tools for ChIP-Seq spike-in assessment and analysis through a versatile collection of graphical functions.

  • CTDquerier Package to retrieve and visualize data from the Comparative Toxicogenomics Database ( The downloaded data is formated as DataFrames for further downstream analyses.

  • CytoDx This package provides functions that predict clinical outcomes using single cell data (such as flow cytometry data, RNA single cell sequencing data) without the requirement of cell gating or clustering.

  • ddPCRclust The ddPCRclust algorithm can automatically quantify the CPDs of non-orthogonal ddPCR reactions with up to four targets. In order to determine the correct droplet count for each target, it is crucial to both identify all clusters and label them correctly based on their position. For more information on what data can be analyzed and how a template needs to be formatted, please check the vignette.

  • DEComplexDisease It is designed to find the differential expressed genes (DEGs) for complex disease, which is characterized by the heterogeneous genomic expression profiles. Different from the established DEG analysis tools, it does not assume the patients of complex diseases to share the common DEGs. By applying a bi-clustering algorithm, DECD finds the DEGs shared by as many patients. In this way, DECD describes the DEGs of complex disease in a novel syntax, e.g. a gene list composed of 200 genes are differentially expressed in 30% percent of studied complex disease. Applying the DECD analysis results, users are possible to find the patients affected by the same mechanism based on the shared signatures.

  • decontam Simple statistical identification of contaminating sequence features in marker-gene or metagenomics data. Works on any kind of feature derived from environmental sequencing data (e.g. ASVs, OTUs, taxonomic groups, MAGs,…). Requires DNA quantitation data or sequenced negative control samples.

  • DEScan2 Integrated peak and differential caller, specifically designed for broad epigenomic signals.

  • DEsingle DEsingle is an R package for differential expression (DE) analysis of single-cell RNA-seq (scRNA-seq) data. It defines and detects 3 types of differentially expressed genes between two groups of single cells, with regard to different expression status (DEs), differential expression abundance (DEa), and general differential expression (DEg). DEsingle employs Zero-Inflated Negative Binomial model to estimate the proportion of real and dropout zeros and to define and detect the 3 types of DE genes. Results showed that DEsingle outperforms existing methods for scRNA-seq DE analysis, and can reveal different types of DE genes that are enriched in different biological functions.

  • diffcoexp A tool for the identification of differentially coexpressed links (DCLs) and differentially coexpressed genes (DCGs). DCLs are gene pairs with significantly different correlation coefficients under two conditions. DCGs are genes with significantly more DCLs than by chance.

  • diffcyt Statistical methods for differential discovery in high-dimensional cytometry (including flow cytometry, mass cytometry or CyTOF, and oligonucleotide-tagged cytometry) using high-resolution clustering and moderated tests.

  • dmrseq This package implements an approach for scanning the genome to detect and perform accurate inference on differentially methylated regions from Whole Genome Bisulfite Sequencing data. The method is based on comparing detected regions to a pooled null distribution, that can be implemented even when as few as two samples per population are available. Region-level statistics are obtained by fitting a generalized least squares (GLS) regression model with a nested autoregressive correlated error structure for the effect of interest on transformed methylation proportions.

  • DominoEffect The functions support identification and annotation of hotspot residues in proteins. These are individual amino acids that accumulate mutations at a much higher rate than their surrounding regions.

  • drawProteins This package draws protein schematics from Uniprot API output. From the JSON returned by the GET command, it creates a dataframe from the Uniprot Features API. This dataframe can then be used by geoms based on ggplot2 and base R to draw protein schematics.

  • DropletUtils Provides a number of utility functions for handling single-cell (RNA-seq) data from droplet technologies such as 10X Genomics. This includes data loading, identification of cells from empty droplets, removal of barcode-swapped pseudo-cells, and downsampling of the count matrix.

  • enrichplot The ‘enrichplot’ package implements several visualization methods for interpreting functional enrichment results obtained from ORA or GSEA analysis. All the visualization methods are developed based on ‘ggplot2’ graphics.

  • FELLA Enrichment of metabolomics data using KEGG entries. Given a set of affected compounds, FELLA suggests affected reactions, enzymes, modules and pathways using label propagation in a knowledge model network. The resulting subnetwork can be visualised and exported.

  • GARS Feature selection aims to identify and remove redundant, irrelevant and noisy variables from high-dimensional datasets. Selecting informative features affects the subsequent classification and regression analyses by improving their overall performances. Several methods have been proposed to perform feature selection: most of them relies on univariate statistics, correlation, entropy measurements or the usage of backward/forward regressions. Herein, we propose an efficient, robust and fast method that adopts stochastic optimization approaches for high-dimensional. GARS is an innovative implementation of a genetic algorithm that selects robust features in high-dimensional and challenging datasets.

  • GateFinder Given a vector of cluster memberships for a cell population, identifies a sequence of gates (polygon filters on 2D scatter plots) for isolation of that cell type.

  • GDCRNATools This is an easy-to-use package for downloading, organizing, and integrative analyzing RNA expression data in GDC with an emphasis on deciphering the lncRNA-mRNA related ceRNA regulatory network in cancer. Three databases of lncRNA-miRNA interactions including spongeScan, starBase, and miRcode, as well as three databases of mRNA-miRNA interactions including miRTarBase, starBase, and miRcode are incorporated into the package for ceRNAs network construction. limma, edgeR, and DESeq2 can be used to identify differentially expressed genes/miRNAs. Functional enrichment analyses including GO, KEGG, and DO can be performed based on the clusterProfiler and DO packages. Both univariate CoxPH and KM survival analyses of multiple genes can be implemented in the package. Besides some routine visualization functions such as volcano plot, bar plot, and KM plot, a few simply shiny apps are developed to facilitate visualization of results on a local webpage.

  • GDSArray GDS files are widely used to represent genotyping or sequence data. The GDSArray package implements the GDSArray class to represent nodes in GDS files in a matrix-like representation that allows easy manipulation (e.g., subsetting, mathematical transformation) in R. The data remains on disk until needed, so that very large files can be processed.

  • GeneStructureTools GeneStructureTools can be used to create in silico alternative splicing events, and analyse potential effects this has on functional gene products.

  • gep2pep Pathway Expression Profiles (PEPs) are based on the expression of pathways (defined as sets of genes) as opposed to individual genes. This package converts gene expression profiles to PEPs and performs enrichment analysis of both pathways and experimental conditions, such as “drug set enrichment analysis” and “gene2drug” drug discovery analysis respectively.

  • GOfuncR GOfuncR performs a gene ontology enrichment analysis based on the ontology enrichment software FUNC. GO-annotations are obtained from OrganismDb or OrgDb packages (‘Homo.sapiens’ by default); the GO-graph is included in the package and updated regularly (10-Apr-2018). GOfuncR provides the standard candidate vs. background enrichment analysis using the hypergeometric test, as well as three additional tests: (i) the Wilcoxon rank-sum test that is used when genes are ranked, (ii) a binomial test that is used when genes are associated with two counts and (iii) a Chi-square or Fisher’s exact test that is used in cases when genes are associated with four counts. To correct for multiple testing and interdependency of the tests, family-wise error rates are computed based on random permutations of the gene-associated variables. GOfuncR also provides tools for exploring the ontology graph and the annotations, and options to take gene-length or spatial clustering of genes into account. From version 0.99.14 on it is also possible to provide custom annotations and ontologies.

  • GSEABenchmarkeR The GSEABenchmarkeR package implements an extendable framework for reproducible evaluation of set- and network-based methods for enrichment analysis of gene expression data. This includes support for the efficient execution of these methods on comprehensive real data compendia (microarray and RNA-seq) using parallel computation on standard workstations and institutional computer grids. Methods can then be assessed with respect to runtime, statistical significance, and relevance of the results for the phenotypes investigated.

  • gsean Biological molecules in a living organism seldom work individually. They usually interact each other in a cooperative way. Biological process is too complicated to understand without considering such interactions. Thus, network-based procedures can be seen as powerful methods for studying complex process. However, many methods are devised for analyzing individual genes. It is said that techniques based on biological networks such as gene co-expression are more precise ways to represent information than those using lists of genes only. This package is aimed to integrate the gene expression and biological network. A biological network is constructed from gene expression data and it is used for Gene Set Enrichment Analysis.

  • hipathia Hipathia is a method for the computation of signal transduction along signaling pathways from transcriptomic data. The method is based on an iterative algorithm which is able to compute the signal intensity passing through the nodes of a network by taking into account the level of expression of each gene and the intensity of the signal arriving to it. It also provides a new approach to functional analysis allowing to compute the signal arriving to the functions annotated to each pathway.

  • hmdbQuery Define utilities for exploration of human metabolome database, including functions to retrieve specific metabolite entries and data snapshots with pairwise associations (metabolite-gene,-protein,-disease).

  • iCNV Integrative copy number variation (CNV) detection from multiple platform and experimental design.

  • igvR Access to igv.js, the Integrative Genomics Viewer running in a web browser.

  • IMMAN Reconstructing Interlog Protein Network (IPN) integrated from several Protein protein Interaction Networks (PPINs). Using this package, overlaying different PPINs to mine conserved common networks between diverse species will be applicable.

  • InTAD The package is focused on the detection of correlation between expressed genes and selected epigenomic signals i.e. enhancers obtained from ChIP-seq data within topologically associated domains (TADs). Various parameters can be controlled to investigate the influence of external factors and visualization plots are available for each analysis step.

  • iSEE Provides functions for creating an interactive Shiny-based graphical user interface for exploring data stored in SummarizedExperiment objects, including row- and column-level metadata. Particular attention is given to single-cell data in a SingleCellExperiment object with visualization of dimensionality reduction results.

  • iteremoval The package provides a flexible algorithm to screen features of two distinct groups in consideration of overfitting and overall performance. It was originally tailored for methylation locus screening of NGS data, and it can also be used as a generic method for feature selection. Each step of the algorithm provides a default method for simple implemention, and the method can be replaced by a user defined function.

  • kissDE Retrieves condition-specific variants in RNA-seq data (SNVs, alternative-splicings, indels). It has been developed as a post-treatment of ‘KisSplice’ but can also be used with user’s own data.

  • LineagePulse LineagePulse is a differential expression and expression model fitting package tailored to single-cell RNA-seq data (scRNA-seq). LineagePulse accounts for batch effects, drop-out and variable sequencing depth. One can use LineagePulse to perform longitudinal differential expression analysis across pseudotime as a continuous coordinate or between discrete groups of cells (e.g. pre-defined clusters or experimental conditions). Expression model fits can be directly extracted from LineagePulse.

  • loci2path loci2path performs statistics-rigorous enrichment analysis of eQTLs in genomic regions of interest. Using eQTL collections provided by the Genotype-Tissue Expression (GTEx) project and pathway collections from MSigDB.

  • MACPET The MACPET package can be used for binding site analysis for ChIA-PET data. MACPET reads ChIA-PET data in BAM or SAM format and separates the data into Self-ligated, Intra- and Inter-chromosomal PETs. Furthermore, MACPET breaks the genome into regions and applies 2D mixture models for identifying candidate peaks/binding sites using skewed generalized students-t distributions (SGT). It then uses a local poisson model for finding significant binding sites. MACPET is mainly written in C++, and it supports the BiocParallel package.

  • MAGeCKFlute MAGeCKFlute is designed to surporting downstream analysis, utilizing the gene summary data provided through MAGeCK or MAGeCK-VISPR. Quality control, normalization, and screen hit identification for CRISPR screen data are performed in pipeline. Identified hits within the pipeline are categorized based on experimental design, and are subsequently interpreted by functional enrichment analysis.

  • martini martini deals with the low power inherent to GWAS studies by using prior knowledge represented as a network. SNPs are the vertices of the network, and the edges represent biological relationships between them (genomic adjacency, belonging to the same gene, physical interaction between protein products). The network is scanned using SConES, which looks for groups of SNPs maximally associated with the phenotype, that form a close subnetwork.

  • mCSEA Identification of diferentially methylated regions (DMRs) in predefined regions (promoters, CpG islands…) from the human genome using Illumina’s 450K or EPIC microarray data. Provides methods to rank CpG probes based on linear models and includes plotting functions.

  • mdp The Molecular Degree of Perturbation webtool quantifies the heterogeneity of samples. It takes a data.frame of omic data that contains at least two classes (control and test) and assigns a score to all samples based on how perturbed they are compared to the controls. It is based on the Molecular Distance to Health (Pankla et al. 2009), and expands on this algorithm by adding the options to calculate the z-score using the modified z-score (using median absolute deviation), change the z-score zeroing threshold, and look at genes that are most perturbed in the test versus control classes.

  • MDTS A package for the detection of de novo copy number deletions in targeted sequencing of trios with high sensitivity and positive predictive value.

  • MetaNeighbor MetaNeighbor allows users to quantify cell type replicability across datasets using neighbor voting.

  • missRows The missRows package implements the MI-MFA method to deal with missing individuals (‘biological units’) in multi-omics data integration. The MI-MFA method generates multiple imputed datasets from a Multiple Factor Analysis model, then the yield results are combined in a single consensus solution. The package provides functions for estimating coordinates of individuals and variables, imputing missing individuals, and various diagnostic plots to inspect the pattern of missingness and visualize the uncertainty due to missing values.

  • MSstatsQCgui MSstatsQCgui is a Shiny app which provides longitudinal system suitability monitoring and quality control tools for proteomic experiments.

  • netSmooth netSmooth is an R package for network smoothing of single cell RNA sequencing data. Using bio networks such as protein-protein interactions as priors for gene co-expression, netsmooth improves cell type identification from noisy, sparse scRNAseq data.

  • OmaDB A package for the orthology prediction data download from OMA database.

  • omicplotR A Shiny app for visual exploration of omic datasets as compositions, and differential abundance analysis using ALDEx2. Useful for exploring RNA-seq, meta-RNA-seq, 16s rRNA gene sequencing with visualizations such as principal component analysis biplots (coloured using metadata for visualizing each variable), dendrograms and stacked bar plots, and effect plots (ALDEx2). Input is a table of counts and metadata file (if metadata exists), with options to filter data by count or by metadata to remove low counts, or to visualize select samples according to selected metadata.

  • omicsPrint omicsPrint provides functionality for cross omic genetic fingerprinting, for example, to verify sample relationships between multiple omics data types, i.e. genomic, transcriptomic and epigenetic (DNA methylation).

  • ORFik Tools for manipulation of RiboSeq, RNASeq and CageSeq data. ORFik is extremely fast through use of C, data.table and GenomicRanges. Package allows to reassign starts of the transcripts with the use of CageSeq data, automatic shifting of RiboSeq reads, finding of Open Reading Frames for the whole genomes and many more.

  • perturbatr perturbatr does stage-wise analysis of large-scale genetic perturbation screens for integrated data sets consisting of multiple screens. For multiple integrated perturbation screens a hierarchical model that considers the variance between different biological conditions is fitted. The resulting list of gene effects is then further extended using a network propagation algorithm to correct for false negatives.

  • phantasus Phantasus is a web-application for visual and interactive gene expression analysis. Phantasus is based on Morpheus – a web-based software for heatmap visualisation and analysis, which was integrated with an R environment via OpenCPU API. Aside from basic visualization and filtering methods, R-based methods such as k-means clustering, principal component analysis or differential expression analysis with limma package are supported.

  • plyranges A dplyr-like interface for interacting with the common Bioconductor classes Ranges and GenomicRanges. By providing a grammatical and consistent way of manipulating these classes their accessiblity for new Bioconductor users is hopefully increased.

  • pogos Provide simple utilities for querying bhklab PharmacoDB, modeling API outputs, and integrating to cell and compound ontologies.

  • PowerExplorer Estimate and predict power among groups and multiple sample sizes with simulated data, the simulations are operated based on distribution parameters estimated from the provided input dataset.

  • powerTCR This package provides a model for the clone size distribution of the TCR repertoire. Further, it permits comparative analysis of TCR repertoire libraries based on theoretical model fits.

  • RandomWalkRestartMH This package performs Random Walk with Restart on multiplex and heterogeneous networks. It is described in the following article: “Random Walk With Restart On Multiplex And Heterogeneous Biological Networks”.

  • RcisTarget RcisTarget identifies transcription factor binding motifs (TFBS) over-represented on a gene list. In a first step, RcisTarget selects DNA motifs that are significantly over-represented in the surroundings of the transcription start site (TSS) of the genes in the gene-set. This is achieved by using a database that contains genome-wide cross-species rankings for each motif. The motifs that are then annotated to TFs and those that have a high Normalized Enrichment Score (NES) are retained. Finally, for each motif and gene-set, RcisTarget predicts the candidate target genes (i.e. genes in the gene-set that are ranked above the leading edge).

  • Rgin C++ implementation of SConES.

  • RGMQL This package brings the GenoMetric Query Language (GMQL) functionalities into the R environment. GMQL is a high-level, declarative language to manage heterogeneous genomic datasets for biomedical purposes, using simple queries to process genomic regions and their metadata and properties. GMQL adopts algorithms efficiently designed for big data using cloud-computing technologies (like Apache Hadoop and Spark) allowing GMQL to run on modern infrastructures, in order to achieve scalability and high performance. It allows to create, manipulate and extract genomic data from different data sources both locally and remotely. Our RGMQL functions allow complex queries and processing leveraging on the R idiomatic paradigm. The RGMQL package also provides a rich set of ancillary classes that allow sophisticated input/output management and sorting, such as: ASC, DESC, BAG, MIN, MAX, SUM, AVG, MEDIAN, STD, Q1, Q2, Q3 (and many others). Note that many RGMQL functions are not directly executed in R environment, but are deferred until real execution is issued.

  • RNAdecay RNA degradation is monitored through measurement of RNA abundance after inhibiting RNA synthesis. This package has functions and example scripts to facilitate (1) data normalization, (2) data modeling using constant decay rate or time-dependent decay rate models, (3) the evaluation of treatment or genotype effects, and (4) plotting of the the data and models. Data Normalization: functions and scripts make easy the normalization to the initial (T0) RNA abundance, as well as a method to correct for artificial inflation of Reads per Million (RPM) abundance in global assesements as the total size of the RNA pool deacreases. Modeling: Normalized data is then modeled using maximum likelihood to fit parameters. For making treatment or genotype comparisons (up to four), the modeling step models all possible treatement effects on each gene by repeating the modeling with constraints on the model parameters (i.e., the decay rate of treatments A and B are modeled once with them being equal and again allowing them to both vary independently). Model Selection: The AICc value is calculated for each model, and the model with the lowest AICc is chosen. Modeling results of selected models are then compiled into a single data frame. Graphical Plotting: a function is provided to easily visualize the data and the selected model using ggplot2 package functions.

  • RSeqAn Headers from the SeqAn C++ library for easy of usage in R.

  • rWikiPathways Use this package to interface with the WikiPathways API.

  • scFeatureFilter An R implementation of the correlation-based method developed in the Joshi laboratory to analyse and filter processed single-cell RNAseq data. It returns a filtered version of the data containing only genes expression values unaffected by systematic noise.

  • scmeth Functions to analyze methylation data can be found here. Some functions are relevant for single cell methylation data but most other functions can be used for any methylation data. Highlight of this workflow is the comprehensive quality control report.

  • Sconify This package does k-nearest neighbor based statistics and visualizations with flow and mass cytometery data. This gives tSNE maps”fold change” functionality and provides a data quality metric by assessing manifold overlap between fcs files expected to be the same. Other applications using this package include imputation, marker redundancy, and testing the relative information loss of lower dimension embeddings compared to the original manifold.

  • SDAMS This Package utilizes a Semi-parametric Differential Abundance analysis (SDA) method for metabolomics and proteomics data from mass spectrometry. SDA is able to robustly handle non-normally distributed data and provides a clear quantification of the effect size.

  • SEPIRA SEPIRA (Systems EPigenomics Inference of Regulatory Activity) is an algorithm that infers sample-specific transcription factor activity from the genome-wide expression or DNA methylation profile of the sample.

  • seqsetvis seqsetvis enables the visualization and analysis of multiple genomic datasets. Although seqsetvis was designed for the comparison of mulitple ChIP-seq datasets, this package is domain-agnostic and allows the processing of multiple genomic coordinate files (bed-like files) and signal files (bigwig files or bam pileups).

  • sevenC Chromatin looping is an essential feature of eukaryotic genomes and can bring regulatory sequences, such as enhancers or transcription factor binding sites, in the close physical proximity of regulated target genes. Here, we provide sevenC, an R package that uses protein binding signals from ChIP-seq and sequence motif information to predict chromatin looping events. Cross-linking of proteins that bind close to loop anchors result in ChIP-seq signals at both anchor loci. These signals are used at CTCF motif pairs together with their distance and orientation to each other to predict whether they interact or not. The resulting chromatin loops might be used to associate enhancers or transcription factor binding sites (e.g., ChIP-seq peaks) to regulated target genes.

  • SIAMCAT Pipeline for Statistical Inference of Associations between Microbial Communities And host phenoTypes (SIAMCAT). A primary goal of analyzing microbiome data is to determine changes in community composition that are associated with environmental factors. In particular, linking human microbiome composition to host phenotypes such as diseases has become an area of intense research. For this, robust statistical modeling and biomarker extraction toolkits are crucially needed. SIAMCAT provides a full pipeline supporting data preprocessing, statistical association testing, statistical modeling (LASSO logistic regression) including tools for evaluation and interpretation of these models (such as cross validation, parameter selection, ROC analysis and diagnostic model plots).

  • signet An R package to detect selection in biological pathways. Using gene selection scores and biological pathways data, one can search for high-scoring subnetworks of genes within pathways and test their significance.

  • singleCellTK Run common single cell analysis directly through your browser including differential expression, downsampling analysis, and clustering.

  • singscore A simple single-sample gene signature scoring method that uses rank-based statistics to analyze the sample’s gene expression profile. It scores the expression activities of gene sets at a single-sample level.

  • SparseSignatures Point mutations occurring in a genome can be divided into 96 categories based on the base being mutated, the base it is mutated into and its two flanking bases. Therefore, for any patient, it is possible to represent all the point mutations occurring in that patient’s tumor as a vector of length 96, where each element represents the count of mutations for a given category in the patient. A mutational signature represents the pattern of mutations produced by a mutagen or mutagenic process inside the cell. Each signature can also be represented by a vector of length 96, where each element represents the probability that this particular mutagenic process generates a mutation of the 96 above mentioned categories. In this R package, we provide a set of functions to extract and visualize the mutational signatures that best explain the mutation counts of a large number of patients.

  • srnadiff Differential expression of small RNA-seq when reference annotation is not given.

  • SummarizedBenchmark This package defines the BenchDesign and SummarizedBenchmark classes for building, executing, and evaluating benchmark experiments of computational methods. The SummarizedBenchmark class extends the RangedSummarizedExperiment object, and is designed to provide infrastructure to store and compare the results of applying different methods to a shared data set. This class provides an integrated interface to store metadata such as method parameters and software versions as well as ground truths (when these are available) and evaluation metrics.

  • TCGAutils A suite of helper functions for checking and manipulating TCGA data including data obtained from the curatedTCGAData experiment package. These functions aim to simplify and make working with TCGA data more manageable.

  • TFEA.ChIP Package to analize transcription factor enrichment in a gene set using data from ChIP-Seq experiments.

  • TFutils Package to work with TF data.

  • TissueEnrich The TissueEnrich package is used to calculate enrichment of tissue-specific genes in a set of input genes. For example, the user can input the most highly expressed genes from RNA-Seq data, or gene co-expression modules to determine which tissue-specific genes are enriched in those datasets. Tissue-specific genes were defined by processing RNA-Seq data from the Human Protein Atlas (HPA) (Uhlén et al. 2015), GTEx (Ardlie et al. 2015), and mouse ENCODE (Shen et al. 2012) using the algorithm from the HPA (Uhlén et al. 2015).The hypergeometric test is being used to determine if the tissue-specific genes are enriched among the input genes. Along with tissue-specific gene enrichment, the TissueEnrich package can also be used to define tissue-specific genes from expression datasets provided by the user, which can then be used to calculate tissue-specific gene enrichments.

  • Trendy Trendy implements segmented (or breakpoint) regression models to estimate breakpoints which represent changes in expression for each feature/gene in high throughput data with ordered conditions.

  • tRNAscanImport The package imports the result of tRNAscan-SE as a GRanges object.

  • TTMap TTMap is a clustering method that groups together samples with the same deviation in comparison to a control group. It is specially useful when the data is small. It is parameter free.

  • TxRegInfra This package provides interfaces to genomic metadata employed in regulatory network creation, with a focus on noSQL solutions. Currently quantitative representations of eQTLs, DnaseI hypersensitivity sites and digital genomic footprints are assembled using an out-of-memory extension of the RaggedExperiment API.

  • vidger The aim of vidger is to rapidly generate information-rich visualizations for the interpretation of differential gene expression results from three widely-used tools: Cuffdiff, DESeq2, and edgeR.

New Data Experiment Packages

There are 16 new data experiment packages in this release of Bioconductor.

  • ASICSdata 1D NMR example spectra and additional data for use with the ASICS package. Raw 1D Bruker spectral data files were found in the MetaboLights database (, study MTBLS1).

  • BloodCancerMultiOmics2017 The package contains data of the Primary Blood Cancer Encyclopedia (PACE) project together with a complete executable transcript of the statistical analysis and reproduces figures presented in the paper “Drug-perturbation-based stratification of blood cancer” by Dietrich S, Oles M, Lu J et al., J. Clin. Invest. (2018) 128(1):427-445. doi:10.1172/JCI93801.

  • This package contains annotation and metagene profile data for the ChIC package.

  • CLLmethylation The package includes DNA methylation data for the primary Chronic Lymphocytic Leukemia samples included in the Primary Blood Cancer Encyclopedia (PACE) project. Raw data from the 450k DNA methylation arrays is stored in the European Genome-Phenome Archive (EGA) under accession number EGAS0000100174. For more information concerning the project please refer to the paper “Drug-perturbation-based stratification of blood cancer” by Dietrich S, Oles M, Lu J et al., J. Clin. Invest. (2018) and R/Bioconductor package BloodCancerMultiOmics2017.

  • HDCytoData Data package containing a set of high-dimensional cytometry data sets saved in SummarizedExperiment and flowSet Bioconductor object formats, including row and column meta-data describing samples, cell populations (clusters), and protein markers.

  • hgu133plus2CellScore The CellScore Standard Dataset contains expression data from a wide variety of human cells and tissues, which should be used as standard cell types in the calculation of the CellScore. All data was curated from public databases such as Gene Expression Omnibus ( or ArrayExpress ( This standard dataset only contains data from the Affymetrix GeneChip Human Genome U133 Plus 2.0 microarrays. Samples were manually annotated using the database information or consulting the publications in which the datasets originated. The sample annotations are stored in the phenoData slot of the expressionSet object. Raw data (CEL files) were processed with the affy package to generate present/absent calls (mas5calls) and background-subtracted values, which were then normalized by the R-package yugene to yield the final expression values for the standard expression matrix. The annotation table for the microarray was retrieved from the BioC annotation package hgu133plus2. All data are stored in an expressionSet object.

  • HMP16SData HMP16SData is a Bioconductor ExperimentData package of the Human Microbiome Project (HMP) 16S rRNA sequencing data for variable regions 1–3 and 3–5. Raw data files are provided in the package as downloaded from the HMP Data Analysis and Coordination Center. Processed data is provided as SummarizedExperiment class objects via ExperimentHub.

  • mCSEAdata Data objects necessary to some mCSEA package functions. There are also example data objects to illustrate mCSEA package functionality.

  • MetaGxBreast A collection of Breast Cancer Transcriptomic Datasets that are part of the MetaGxData package compendium.

  • MetaGxOvarian A collection of Ovarian Cancer Transcriptomic Datasets that are part of the MetaGxData package compendium.

  • MetaGxPancreas A collection of pancreatic Cancer transcriptomic datasets that are part of the MetaGxData package compendium.

  • RcisTarget.hg19.motifDBs.cisbpOnly.500bp RcisTarget databases: Gene-based motif rankings and annotation to transcription factors. This package contains a subset of 4.6k motifs (cisbp motifs), scored only within 500bp upstream and the TSS. See RcisTarget tutorial to download the full databases, containing 20k motifs and search space up to 10kbp around the TSS.

  • RGMQLlib A package that contains scala libraries to call GMQL from R used by RGMQL package. It contains a scalable data management engine written in Scala programming language.

  • Supporting data for the TCGAbiolinksGUI package. It includes the following objects: glioma.gcimp.model, glioma.idhwt.model glioma.idhmut.model,glioma.idh.mode, probes2rm, maf.tumor,GDCdisease.

  • TENxBrainData Single-cell RNA-seq data for 1.3 million brain cells from E18 mice, generated by 10X Genomics.

  • tissueTreg The package provides ready to use epigenomes (obtained from TWGBS) and transcriptomes (RNA-seq) from various tissues as obtained in the study (Delacher and Imbusch 2017, PMID: 28783152). Regulatory T cells (Treg cells) perform two distinct functions: they maintain self-tolerance, and they support organ homeostasis by differentiating into specialized tissue Treg cells. The underlying dataset characterises the epigenetic and transcriptomic modifications for specialized tissue Treg cells.

New Workflows

  • BiocMetaWorkflow Bioconductor Workflow describing how to use BiocWorkflowTools to work with a single R Markdown document to submit to both Bioconductor and F1000Research.

  • simpleSingleCell This workflow implements a low-level analysis pipeline for scRNA-seq data using scran, scater and other Bioconductor packages. It describes how to perform quality control on the libraries, normalization of cell-specific biases, basic data exploration and cell cycle phase identification. Procedures to detect highly variable genes, significantly correlated genes and subpopulation-specific marker genes are also shown. These analyses are demonstrated on a range of publicly available scRNA-seq data sets.

NEWS from new and existing Software Packages


Version: 2017-12-18 Date: 2017-12-18 Category: Updating! Refine qtotal (R funtion: qtotalNormalized Text:

Version: 2017-07-18 Date: 2017-07-18 Category: Updating! Adapt aFold model for complex design with linear model (R funtion: ABSSeqlm Text:

Version: 2017-06-02 Date: 2017-06-02 Text: 1) Updating! Introduce a new approach for normalization as qtotal (R funtion: qtotalNormalized) 2) aFold now moderates fold changes upon overall dispersion and gene-specific dispersion

Version: 2017-02-14 Date: 2017-02-14 Category: Updating! Adding new method: aFold to call DE via fold-change Text:


Changes in version 2.19.2 (2018-04-19):

  • More on warning on Windows in linking from Rd files.

Changes in version 2.19.1 (2018-04-17):

  • Prevent warning on Windows in linking from Rd files.


Changes in version 1.0.0:

  • The first release of this package was made as part of Bioconductor 3.7, in April 2018. The adaptest R package provides routines for the method first described in the the technical manuscript 1 and the software paper 2: 1. Weixin Cai, Nima S. Hejazi, Alan E. Hubbard. Data-adaptive statistics for multiple hypothesis testing in high-dimensional settings. 2. Weixin Cai, Alan E. Hubbard, Nima S. Hejazi. adaptest: Data-Adaptive Statistics for High-Dimensional Testing in R.


Version: 1.52.0 Category: Changed plotting for makeImages to use ggplot2 rather than lattice

Version: 1.52.0 Category: Added a new function, vennInLine, intended to allow for placement of

Version: 1.52.0 Category: Venn diagrams in Rmarkdown-derived HTML documents, particularly those

Version: 1.52.0 Category: that use the BiocStyle package for formatting. The Venn diagrams

Version: 1.52.0 Category: contain clickable links that will open HTML tables containing results

Version: 1.52.0 Category: for the genes that are found within that cell of the diagram


Changes in version 1.10.1:

  • fixed a bug whereby the order of samples affected the centring of the data


Changes in version 1.1.2:

  • ampliCan supports now other aligners with SAM format eg. bwa mem (cigarsToEvents) and pair format eg. EMBOSS needleall (pairToEvents)

  • HDR quantification

  • more then 10x speed up of extracting events from alignments


Changes in version 1.7.2:


  • New method ‘edivisive’ available.

  • Breakpoint detection available for both Aneufinder(…, strandseq=TRUE) and Aneufinder(…, strandseq=FALSE)

  • A stepsize for a sliding window can be selected in addition to the binsize for method “HMM”. This improves resolution of detected breakpoints.

  • Breakpoints for Aneufinder(…, strandseq=TRUE) are reported with confidence intervals in folder BROWSERFILES.

  • Breakpoint detection for Aneufinder(…, strandseq=TRUE) has an additional breakpoint refinement step which improves localization of breakpoints.


  • Reorganized output folder structure and added README.txt

  • Renamed parameter “plot.SCE” to “plot.breakpoints”.

  • GC correction is now done with a loess-fit by default instead of the quadratic fit. This should improve accuracy.

  • Default epsilon is now ‘eps=0.01’ (was ‘eps=0.1’ before) for method “HMM”.


Changes in version 1.3.1:


  • Add DoubleFilter


Changes in version 2.12.0:


  • Prompt for permission when downloading many (more than AnnotationHubOption(“MAX_DOWNLOADS”)) resources.


  • Moved readMetadataFromCsv back to AnnotationHubData.

  • Use AnnotationHubData::makeAnnotationHubMetadata to validate metadata.csv


Changes in version 1.10.0:


  • Moved readMetadataFromCsv back to AnnotationHubData.

  • Use AnnotationHubData::makeAnnotationHubMetadata to validate metadata.csv

  • readMetadataFromCsv is now internal function


Changes in version 1.6.0:


  • Add support for chicken (galGal5).


  • Add the ability to facet over two variables in plot_numerical().

  • Add the ability to keep duplicate regions in summarize_categorical() and plot_categorical(). This is accomplished with the ‘by’ parameter in the former and by the ‘x’ and ‘fill’ parameters in the latter, and passing their contents into the ‘.dots’ parameter of dplyr::distinct_().

  • Make TxDb and OrgDb packages Suggests instead of Imports. NOTE: This saves space, but also requires downloading the appropriate packages as needed.

  • Add list_env() function to the annotatr_cache environment to see what custom annotations have been read in and added to the cache.


  • Replace dplyr::summarize_each_() with dplyr::summarize_at() in line with deprecation in the dplyr package.

  • Prefix builtin_ functions with annotatr:: so that packages that Import annotatr don’t encounter errors.


Changes in version 1.0.1:

  • We changes semantics buffering down into buffered (mRNA up) and buffering up into buffered (mRNA down) - so the interpretation is more intuitive.

  • Add customization options to anota2seqPlotFC and anotat2seqPlotPvalues functions

  • Fixed a bug where an unitialized object “regModes” was being accessed causing an uninformative error message.


Changes in version 3.9.1 (2017-12-19):


  • robustSmoothSpline() now supports using Tukey’s biweight (in addition to already exising L1) estimators. See argument ‘method’. Thanks to Aaron Lun at the Cancer Research UK Cambridge Institute for adding this feature.

Changes in version 3.9.0 (2017-10-30):

  • The version number was bumped for the Bioconductor devel version, which is now BioC 3.7 for R (>= 3.5.0).


Version: 0.99.0 Category: First version submitted to Bioconductor Text:

Version: 0.99.0 Category: New features Text: preprocessing functions: baseline correction, alignment,

Version: 0.99.0 Category: normalisation Text: library of pure spectra management functions

Version: 0.99.0 Category: normalisation Text: binning algorithm

Version: 0.99.0 Category: normalisation Text: diagnosis tool to assess the quality of the quantification

Version: 0.99.0 Category: normalisation Text: post-quantification statistical analysis functions: PCA, OPLS-DA

Version: 0.99.0 Category: and Kruskal-Wallis test Text:

Version: 0.99.0 Category: Improvements Text: user’s guide

Version: 0.99.0 Category: Improvements Text: spectra quantification

Version: 0.99.0 Category: Improvements Text: parallel with BiocParallel package

Version: 0.99.0 Category: PREVIOUS VERSIONS ON CRAN Text:

Version: 0.99.0 Category: New features Text: data importation from Bruker files

Version: 0.99.0 Category: New features Text: spectra quantification

Version: 0.99.0 Category: New features Text: user’s guide


Changes in version 1.5.1:


  • readCounts supports identical gene names in different chromosomes.

  • Fixed default value for minAnchor argument of readCounts code, man page and vignette.


Version: 1.31.1 Date: 2018-03-28 Category: Fix bug when custom gene set and expression set both have same type of gene IDs


Changes in version 1.2.0:

  • Added shiny app to modify thresholds

  • Added support for sparse matrices (dgCMatrix)

  • New function: AUCell_plotTSNE()

  • AUC values are normalized to max 1 by default.


Changes in version 1.1.63 (2018-04-27):

  • Extra warning message added when scran normalisation fails to produce positive size factors

Changes in version 1.1.62 (2018-04-21):

  • Regression is now a compulsory parameter in BASiCS_MCMC, hidden functions, documentation and unit tests updated accordingly.

  • Minor updates in vignette to clarify default parameter in newBASiCS_Data

  • BASiCS_Filter adapted to no-spikes case and minor bug resolved

  • Added unit test for BASiCS_Filter

  • Minor bug fixed for no-spikes case in BASiCS_DenoisedCounts

Changes in version 1.1.61:

  • Regression is now a compulsory parameter in BASiCS_MCMC, hidden functions and SOME unit tests updated accordingly.

Changes in version 1.1.60 (2018-04-19):

  • Updated DESCRIPTION file to introduce residual over-dispersion testing

Changes in version 1.1.59 (2018-04-19):

  • Documentation of RefFreq in BASiCS_Chain class.

Changes in version 1.1.58 (2018-04-19):

  • Updates in vignette to fully incorporate the regression and non-spike BASiCS models.

Changes in version 1.1.57 (2018-04-16):

  • Minor changes in NEWS file

Changes in version 1.1.56 (2018-04-16):

  • Minor changes in BASiCS_MCMCcppNoSpikes.cpp to avoid warnings in BioC

Changes in version 1.1.55 (2018-04-16):

  • Speed-up of BASiCS_TestDE by avoiding unnecessary calculations

Changes in version 1.1.54 (2018-04-15):

  • CITATION file updated to include latest BASiCS bioRxiv preprint

Changes in version 1.1.53 (2018-04-13):

  • Fixed bug in plotting for TestDE function

  • Added extra code in vignette to construct BASiCS_Data with no spikes

  • Added plots to show changes in residual variability during testing

Changes in version 1.1.52 (2018-04-09):

  • Added extra sentence to vignette describing the BASiCS_Data generation when SpikeInfo is not available

Changes in version 1.1.51 (2018-03-26):

  • Adjusted BASiCS_TestDE function to output data.frames containing same genes.

Changes in version 1.1.50 (2018-03-26):

  • Removed OffSet correction for phi in the BASiCS_TestDE function

Changes in version 1.1.49 (2018-03-22):

  • Fixed link to BASiCS_Chain documentation in BASiCS_showFit doc

Changes in version 1.1.48 (2018-03-22):

  • Excluded epsilon object and RefFreq object from validity test in Chain Class

Changes in version 1.1.47 (2018-03-21):

  • Reduced number of genes in data examples

  • Unit test updated accordingly

  • Nils added as maintainer in DESCRIPTION

Changes in version 1.1.46 (2018-03-21):

  • Split C++ code into individual functions

  • One file per main function and individual files for utility function

  • Created header files for main functions and utility functions

Changes in version 1.1.45 (2018-03-21):

  • Messages within C++ code moved to functions

Changes in version 1.1.44 (2018-03-21):

  • HiddenVarDecomp adapted to no-spikes case

  • Unit test for BASiCS_VarDecomp expanded accordingly

  • Specification of colnames and rownames added to newBASiCS_Data

  • colnames and rownames are now specified as part of the output of BASiCS_DenoisedCounts and BASiCS_DenoisedRates

Changes in version 1.1.43 (2018-03-20):

  • Batch information moved to colData instead of metadata when building a SingleCellExperiment object via the newBASiCS_Data function. This facilitates data subsetting.

  • BASiCS_MCMC and HiddenBASiCS_MCMC_InputCheck updated accordingly

  • SummarizedExperiment::colData and S4Vectors::DataFrame added as imports in NAMESPACE

Changes in version 1.1.42 (2018-03-20):

  • OrderVariable default value set as “GeneIndex” in BASiCS_TestDE

  • Fixed usage of OrderVariable in BASiCS_TestDE regression case

  • Associated unit test updated accordingly

  • Missing denoised rates/counts check added to unit tests for no-spikes case

  • CITATION file has been added

Changes in version 1.1.41 (2018-03-20):

  • BASiCS_MCMC: Default value for WithSpikes set as FALSE when there are no spike-ins in available in the data

Changes in version 1.1.40 (2018-03-20):

  • Fixes small bug in BASiCS_DenoisedRates, no-spikes case

  • Adds denoised rates/counts check to unit tests for no-spikes case

Changes in version 1.1.39 (2018-03-20):

  • Denoised counts/rates added to unit test for regression case

  • BASiCS_DenoisedCounts adapted for no-spikes case

  • BASiCS_DenoisedRates adapted for no-spikes case

Changes in version 1.1.38 (2018-03-20):

  • Validity checks updated for BASiCS_Chain and BASiCS_Summary classes. This accounts for different parameter configurations

  • Summary method to exclude RefFreq for the no-spikes case

  • Unit tests fo no-spikes case updated accordingly

Changes in version 1.1.37 (2018-03-20):

  • phi removed from the output of BASiCS_MCMC for no-spikes case

  • Unit tests updated accordingly

  • Checks for parameter names added to unit tests

Changes in version 1.1.36 (2018-03-18):

  • Fixed bug in newBASiCS_Data to define a default value for Tech when spike-ins are not available. Thanks to Muad Abd El Hay (@Cumol) for pointing out this issue.

Changes in version 1.1.35 (2018-03-18):

  • New unit tests (more modular): example data, starting values MCMC, MCMC sampler for fixed starting values (spikes/no-spikes; regression/no-regression)

Changes in version 1.1.34 (2018-01-31):

  • HiddenBASiCS_MCMC_Start edited to account for new default parameter values in scran::computeSumFactors call

  • Unit tests updated accordingly

  • Imports/Suggests packages are now in alphabetic order

  • Minor style changes suggested by BiocCheck

Changes in version 1.1.33 (2018-01-30):

  • In HiddenBASiCS_MCMC_Start, positive = TRUE added to scran::computeSumFactors when estimated size factor contain invalid values. Thanks to Mike Morgan for suggesting this solution.

Changes in version 1.1.32 (2018-01-29):

  • Fix to ensure that BASiCS_MCMC function adds cell labels for $\phi$

  • makeExampleBASiCS_Data now produces valid colnames (cell labels)

  • Fixed colnames of $\phi$ parameter in all data examples

  • Extended validity test for BASiCS_Chain class

  • rownames and colnames methods created for BASiCS_Chain class

  • Added example and unit test for BASiCS_VarianceDecomp function

Changes in version 1.1.31 (2018-01-22):

  • Updated documentation for BASiCS_showFit method

Changes in version 1.1.30 (2018-01-22):

  • Commit to triger a new built

Changes in version 1.1.29 (2017-12-21):

  • showFit generic renamed as BASiCS_showFit (to avoids potential conflicts)

Changes in version 1.1.28 (2017-12-20):

  • Vignette header as in BiocStyle

  • In BASiCS_TestDE function: ProbThresholdE argument renamed as ProbThresholdR

  • In BASiCS_TestDE function: ProbThresholdE argument renamed as ProbThresholdR

  • Updated documentation for example BASiCS_Chain objects

  • Minor additional changes to the documentation

Changes in version 1.1.27 (2017-12-20):

  • Minor typo resolved in displayChainBASiCS method

  • Reduced size of example objects

  • Unit tests updated accordingly

  • In BASiCS_TestDE function: PsiE argument renamed as EpsilonR

Changes in version 1.1.26 (2017-12-20):

  • Vignette bibliography moved to .bib file

  • Added diagram to summarise different implementations

  • Reduced size of example objects

  • Unit tests updated accordingly

  • subset method created for BASiCS_Chain objects

  • Removal of parameter lambda from BASiCS_Chain objects (for storage)

  • R/Methods.R + R/Classes.R updated accordingly

  • newBASiCS_Chain updated accordingly.

  • Code format for showFit

Changes in version 1.1.24 (2017-12-18):

  • Reduced no of iterations in unit test for quicker testing

  • library hexbin added to imports (required for showFit)

  • Vignette edits (simplification of Quick Start)

Changes in version 1.1.23 (2017-12-18):

  • Minor improvements to documentation

Changes in version 1.1.22 (2017-12-15):

  • Documentation on ChainSCReg and ChainRNAReg datasets added

  • Fixed showFit method

  • Updated dpi option in vignette to reduce .html size

  • Default value for ConstrainProp set to 0.20 (no-spikes)

  • Unit tests updated accordingly (no-spikes)

Changes in version 1.1.21 (2017-12-13):

  • ConstrainProp added as an optional argument for BASiCS_MCMC (no-spikes)

Changes in version 1.1.20 (2017-12-11):

  • Updated dpi option in vignette

Changes in version 1.1.19 (2017-12-09):

  • extended vignette to describe regression and non-spike case

  • changed markdown to rmarkdown engine to compile vignette to include table of contents

Changes in version 1.1.18 (2017-12-08):

  • Minor typo in HiddenBASiCS_MCMC_NoSpikesParam resolved

Changes in version 1.1.17 (2017-12-07):

  • Stop scaling of size factors for no-spikes case (HiddenBASiCS_MCMC_Start)

  • Unit testing updated accordingly

  • Extra unit test to ensure that no-spikes results match for objects with/without spikes when setting WithSpikes = FALSE

  • Modified constrain for no-spikes cases (to deal with non-zero genes)

  • Default value of ConstrainType set to 1 in BASiCS_MCMC (no-spikes only)

Changes in version 1.1.16 (2017-11-29):

  • Change in BASiCS_MCMC no-spikes so that only genes with zero total counts are excluded from the identifiability constrain

Changes in version 1.1.15 (2017-11-29):

  • Typo fixed in AtLeast2Cells (BASiCS_MCMC function) definition for no-spikes + regression case when original data has spikes

Changes in version 1.1.14 (2017-11-29):

  • Minor bug resolved for no-spikes case when original data has spikes

  • New unit test to assess that case

Changes in version 1.1.13 (2017-11-28):

  • Fixed storage of RefGene in no-spikes when StochasticRef = FALSE

Changes in version 1.1.12 (2017-11-28):

  • Additional changes to improve usage of no-spikes case

Changes in version 1.1.11 (2017-11-24):

  • Minor typo in the call to HiddenBASiCS_MCMCcppNoSpikes has been resolved

Changes in version 1.1.10 (2017-11-27):

  • HiddenBASiCS_MCMC_Start updated to remove regression-related hyper-params

  • HiddenBASiCS_MCMC_ExtraArgs updated to include regression-related hyper-par

  • BASiCS_MCMC modified accordingly

  • Storage of adaptive variances fixed for the no-spike case

Changes in version 1.1.9 (2017-11-24):

  • means only updated when needed (regression case); unit test updated accordingly

  • deltaUpdateNoSpikes + deltaUpdateRegNoSpikes removed as no longer required

  • Simplification of terms in deltaUpdateReg

  • Small changes to unify code format in C++ file

  • Notation change: phi replaced by s in no-spikes implementation

  • Unit test changed accordingly (no-spike)

  • Minor style changes in BASiCS_MCMC

  • BASiCS_MCMC function broken into smaller functions (easier to read). This creates the following hidden functions: HiddenBASiCS_MCMC_InputCheck, HiddenBASiCS_MCMC_ExtraArgs, HiddenBASiCS_MCMC_NoSpikesParams, HiddenBASiCS_MCMC_OutputStore and HiddenBASiCS_MCMC_RefFreqStore

  • Merge between no-spikes and regression case completed (code to be tested)

  • Minor change in storage of reference frequency (no spikes only)

Changes in version 1.1.8 (2017-11-21):

  • muUpdateRegNoSpikes and deltaUpdateRegNoSpikes added to C++ code

  • Clean-up of C++ code (repeated debug checks made into function)

  • lambdaUpdateReg created as a separate function

  • Vectorization of calculations related to regression implementation

  • Global quantities (e.g. inv(V0)) taken outside the look (regression case)

  • sigma2UpdateReg created as a separate function

  • betaUpdateReg created as a separate function

  • Fixed typo in sigma2 updates (regression case); unit test updated accordingly

Changes in version 1.1.7 (2017-11-20):

  • Nils added as author in cpp file

  • Updated unit test for no-spikes case (changes due to change in stoch ref)

  • Change in BASiCS_MCMC so that only biological counts go to C++

  • Added factorizations in muUpdateReg and deltaUpdateReg (C++ code)

Changes in version 1.1.6 (2017-11-15):

  • Added prototype for regression + no-spikes sampler

Changes in version 1.1.5 (2017-11-15):

  • Removal of collapsed sampler prototype (from C++ and R) - moved to CollapsedSampler branch

  • Number of genes used for stochastic reference increased to 10% of genes (no spikes only)

Changes in version 1.1.4 (2017-11-12):

  • Only include genes that are expressed in at least 2 cells per condition for differential residual dispersion testing (regression case only)

Changes in version 1.1.3 (2017-11-08):

  • Collapsed sampler implemented (to be tested)

  • Unit tests reverted to original case

  • Version number bump

  • Store TableRef on the StoreDir directory (no-spike case only)

Changes in version 1.1.2 (2017-11-08):

  • Skeleton for sampler with integrated out s

Changes in version 1.1.1 (2017-11-08):

  • ‘ggplot2’ added to imports

  • Default value for SpikeInfo changed to NULL in newBASiCS_Data function

  • Cleaning of HiddenBASiCS_MCMCcppNoSpikes

  • Cleaning of full conditionals for no-spikes implementation

  • Fixed bug in stochastic reference implementation

  • Added unit test for no-spikes case (estimation)

  • Minor tyle changes to merge regression case

  • ‘Eta’ parameter removed from Summary method (regression case only)

  • Corrected HPD interval calculation for epsilon and sigma2 (regression case)

  • Added mark for ‘ExcludedFromRegression’ genes in BASiCS_TestDE

Changes in version 1.1.0 (2017-08-16):

  • Minor changes required to pass BiocCheck (used formatR and BiocChecks)

  • Version number bump after bioconductor 3.6 release


Version: 1.0.1 Category: fixed a bug for windows version that caused by pthread Text:

Version: 1.0.2 Category: added helper functions to preprocess user files Text: “trimRead” to trim adpators. “uniqueBar” to extract unique barcode sequence from the library file

Version: 1.0.3 Category: change “alignment” to “mapping” in the title Text:

Version: 1.0.4 Category: change “for” to “in” in the title Text:


Changes in version 1.1.13:

  • Changed environment variable to BEACHMAT_RPATH for consistency with other packages.

  • Added native support for transposition and subsetting in DelayedMatrix objects.

  • Added support for chunk-by-chunk realization of otherwise unsupported matrices, including DelayedMatrix objects with other delayed operations.

  • Added the get_const_col_indexed() method for input matrices, especially fast for sparse representations.

  • Added the set_col_indexed() and set_row_indexed() methods for output matrices.

  • Updated vignettes and expanded the test suite.


Version: 1.7.05 Text: omit importFrom clusterProfiler plot

Version: 1.7.04 Text: export Diagrammer and viNetwork to report

Version: 1.7.04 Text: reset image size of circomics to 1024px

Version: 1.7.03 Text: Save network widgets as HTML and png

Version: 1.7.03 Text: use swithc buttom for Networking Tab.

Version: 1.7.03 Text: setwd(~)/ for windows system by setwd(Sys.getenv(“R_USER”))

Version: 1.7.02 Text: resolve conflicts renderMetabologram and renderCoffeewheel. redefine initCoffeewhell in /htmlwidges

Version: 1.7.02 Text: report circomics widget to markdown document

Version: 1.7.02 Text: Save static wheel as html and png (low resolution)

Version: 1.7.02 Text: need phantomJS to catupe html widget output as png file

Version: 1.7.01 Text: add helps to ? menu

Version: 1.7.01 Text: change stop message

Version: 1.7.01 Text: addResourcePath for figures

Version: 1.7.00 Category: metamorphosis: bioCancer is a extension Text:

Version: 1.7.00 Category: reduce size of package by half 14 -> 7 mb Text:


Changes in version 1.16:


  • handle interactive BiocCheck() arguments correctly


Changes in version 1.3:


  • (v. 1.3.35) Save a post download processed file to cache.

  • (v. 1.3.28) Add ask = TRUE argument to BiocFileCache().

  • (v. 1.3.24) Add function makeBiocFileCacheFromDataFrame to convert data.frame to BiocFileCache

  • (v. 1.3.19) etag now checked in addition to last modified time to determine if local version of file is current

  • (v. 1.3.16) importbfc to load output of exportbfc

  • (v. 1.3.15) exportbfc allows users to create exportable archive of bfc related files

  • (v. 1.3.11) bfcisrelative checks for rtype=’local’ in addition to relative

  • (v. 1.3.11) Helper function to check rtype for local but relative, and web and update if necessary

  • (v. 1.3.10) Add function to check portability of BiocFileCache: bfcisrelative

  • (v. 1.3.10) Add function to convert rpaths for portability: bfcrelative

  • (v. 1.3.9) Optionally download web resource when adding to cache bfcadd(download=TRUE)


  • (v. 1.3.36) expires added

  • (v. 1.3.19) etag added

  • (v. 1.3.9) Last modified time default is NA


  • (v. 1.3.38) … argument exposed and pased to GET, this includes bfcadd which original … was pasesed to file.copy. This use of … is used in bfc functions bfcadd(), bfcupdate() and bfcdownload() which could potential download the file.

  • (v. 1.3.30) bfcnew(), bfcadd(), accept vector arguments; performance improvements and

  • (v. 1.3.25) bfcinfo and bfcquery will show full rpaths even if stored as relative

  • (v. 1.3.22) prompt user only once when using default cache

  • (v. 1.3.17) prompt user when overwriting exisiting file

  • (v. 1.3.16) add importbfc to extract output of exportbfc and load bfc object

  • (v. 1.3.16) added exportbfc to export bfc or subset of bfc

  • (v. 1.3.16) bfcisportblae and bfcportbale removed for exportbfc

  • (v. 1.3.14) upon bfc creation, option to update to most current schema

  • (v. 1.3.13) bfcportable operates over all offending ids instead of asking individually

  • (v. 1.3.12) bfcisrelative/bfcrelative changed to bfcisportbale/bfcportable

  • (v. 1.3.11) web resource rpaths are stored as relative links

  • (v. 1.3.9) If web resource was not downloaded, bfcneedsupdate is TRUE

  • (v. 1.3.9) Local and non downloaded web will have last modified time as NA

  • (v. 1.3.6) Update how default cache location is determined

  • (v. 1.3.1) Expose GET::config argument to web resource functions


  • (v. 1.3.40) correct trycatch with cache_info. cache_info bug workaround orginally output NA even if present, now manually grab values if present

  • (v. 1.3.37) correct which functions update access_time

  • (v. 1.3.26) patch for cache_info after returning etag and last_modified

  • (v. 1.3.4) patch for cache_info bug


Changes in version 1.30.0:


  • biocLite() supports github repositories using the remotes package, rather than devtools. This change should be transparent to end users. (From Peter Hickey


Changes in version 1.14:


  • (v 1.13.1) bpiterate,serial-method does not unlist the result of FUN before passing to REDUCE.


Changes in version 2.8.0:


  • Add ‘relative_path’ argument to ‘pdf_document’

  • Add argument ‘titlecaps’ to ‘html_document’

  • Defunct deprecated functions


  • Fix a bug in generating navigation links which resulted in an empty document when there were no subsections to merge


Changes in version 2.36.0:


  • Patched problem returning the list of available datasets, if the description of one or more datasets included an apostrophe (introduced with new primate species in Ensembl).

  • Caught scenario where ensemblRedirect=FALSE was still being ignored.

  • Changed query submission when redirection is detected to cope with apparently new behaviour of the Ensembl mirrors.


  • Increase query timeout limit to 5 minutes.


Changes in version 1.7.4:


  • unit testing on Windows 32 bits disabled

Changes in version 1.7.2:


  • modification in unit testing


Changes in version 1.4.0:

  • An updated release of this package for Bioconductor 3.7, released April 2018.

  • This release primarily implements minor changes, including the use of colors in the plots produced by the visualization methods.


Changes in version 1.1.2:

  • Removed unneeded so files.


Changes in version 1.6.0:

  • Add additional observation models: “binomial”, “bernoulli”, “beta” and “gaussian”.

  • Add functionlity for Bayesian inference using mean-field variational inference for both inferring and clustering profiles.

  • Add functionality for Fourier basis functions.

  • Update plotting functionality to use ggplot2.


Changes in version 2.1.0:


  • Javascript code uses npm and webpack

  • R code uses latest httpuv from RStudio, with async websocket windows support


Changes in version 0.99:

  • Submitted CAGEfightR to Bioconductor


Changes in version 1.21.6:

  • mergeCAGEsets accepts CAGEexp objects as input.

  • CTSSes are now represented by GPos objects, which are more compact in memory and on display, while still inheriting from GRanges.

Changes in version 1.21.5:

  • Simplified CAGEexp constructor, similar to the one for CAGEset objects.

  • New removeStrandInvaders() function to count and remove strand-invasion artefacts (see Tang et al., 2013, doi:10.1093/nar/gks112).

  • Tag clusters are sorted before being stored in the CAGEr objects.

  • plotAnnot: - new “facet” option for running ggplot2::facet_wrap() on the plots. - better documentation for the “scopes” of the plot. - removed “customScope” argument: pass a function directly to “scope” argument instead.

  • plotCorrelation2: - new methods for SummarizedExperiment, DataFrame, data.frame and matrix. - Corrected the correlation matrix output (previously the diagonal values were 0 and the other values were swapped).

  • plotReverseCumulatives: - fitInRange accepts a value of “NULL” to turn off power law fitting. - New “legend” argument to remove legend when set to “FALSE”. - Axis range and labels can be modified with xlab/ylab and xlim/ylim. - Ladders steps start on the values instead of being centered on.

  • setColors: allow lowercase in color names.

Changes in version 1.21.4:

  • Corrected a bug that was crashing CAGEset objects when loading more than one BAM file.

  • Load BAM as gapped alignment with readGAlignments() instead of scanBam(). Without this correction, TSS position on minus strand is incorrect in case of indels in the read.

  • Partial support for loading BAM data in CAGEexp objects. (correctSystematicG is not yet implemented)

  • Added multicore processing in hanabi function.

Changes in version 1.21.3:

  • Enforce syntactically valid sample names in CAGEexp class.

Changes in version 1.21.2:

  • Use a plain DataFrame as rowData in seqNameTotals slots.

Changes in version 1.21.1:


  • The plotting functions send their output to the graphical device instead of writing it to a file. This makes their use more consistent with most plotting functions in R.


  • New “CAGEexp” class extending the MultiAssayExperiment class. It stores expression data more efficiently than “CAGEset”, and uses core Bioconductor typse natively. For backwards compatibility it also support many of the original generic functions for “CAGEset” objects.

  • New “CTSS” and “TagClusters” classes wrapping GRanges objects, for more type safety.

  • New functions for quality controls such as plotAnnot() or hanabiPlot(). See the CAGEexp vignette for details.

  • Data export as DESeqDataSet object for DESeq2 with the new “consensusClustersDESeq2” and “GeneExpDESeq2” functions.

  • New “bedctss” format to load the FANTOM5 and FANTOM6 CAGE data.

  • New “CAGEscanMolecule” format to load CAGEscan 3.0 data.

  • Multicore parallelisation with BiocParallel instead of parallel.

  • New function sampleList() to help looping on samples with lapply().

  • New plotCorrelation2() function, faster than plotCorrelation() because it is plain black and white.

  • Multicore loading of CTSS data in CAGEexp object.


  • Example data “exampleCAGEexp”, “exampleCAGEexp” and “exampleZv9_annot” are now is lazy-loaded.

  • Passes R CMD check without errors or notes.

  • NULL can be passed as genome name, to circumvent the requirement for a BSgenome object when actually not needing one.

  • In CAGEexp objects, expression quantile positions are given relative to the cluster start site.

  • For performance reasons, the positions of a quantile Q is now calculated as the position of the first base where cumulative expression is higher or equal to Q% of the total expression of a cluster.


  • Roxygen is used to generate the manual pages.

  • A new vignette describes the “CAGEexp” class.


Version: 1.11.01 Text: rm gamma = 1.5 argument for grDevices::rainbow function

Version: 3.1 Text:

Version: 3.2 Text: dimensions levels will be plot. 1- dialogMetOption(): add “Circos” argument to make the difference between getMetDataMultipleGene() and getListMetData() 2- getGeneList(): add rm(“GeneListMSigDB””, envir=”myGlobalEnv”)


Changes in version 1.11.2:


  • Added ‘writeMSIData’, ‘writeImzML’, and ‘writeAnalyze’ methods for writing MSI data to supported file formats

  • Added support for on-disk ‘processed’ imzML (via argument ‘attach.only’ in ‘readImzML’ method)


  • Package ‘matter’ is used for all file I/O now

  • Switched from using ‘Hashmat’ to using ‘sparse_mat’ class from ‘matter’ for ‘processed’ imzML data


  • Changed compiler settings for parsing XML so reading large imzML files should use much less memory now (but may take slightly longer for smaller files)

Changes in version 1.11.1 (2017-10-25):


  • Use ‘drop=NULL’ from now on instead of ‘drop=NA’ to do endomorphic subsetting of ‘SimageData’ objects


  • Use ‘keys’ and ‘keys<-‘ generic from ‘matter’


Changes in version 1.2.0 (2018-04-26):

New Features

  • heatmapOutput() can now determine the heatmap margines and column and row name sizes automatically.

  • New image formats TIFF, JPG and BMP in addition to the previous PNG file format for heatmapOutput(). They can be chosen from processOneStudy() and processMultipleStudies or directly from heatmapOutput() function.

  • heatmapOutput() now uses two methods for ranking the genes prior to generating heatmap(s). One of them is suited for finding genes that have unique high values in one or few cancer studies whereas the other method aids in detemining genes that possess high values in multiple / many cancers.

  • If function argumnets are entered wrongly, more meaningful errors will appear.

  • All functions are improved.


Changes in version 0.99.4 (2018-04-06):


  • Split plot functionality from filter_genes() into plot_genes().

  • Removed file name arguments from read_10x() and write_10x().


Changes in version 1.25.0 (2018-01-10):

  • BUG FIX * fix gray boxes in plotOptimResultsPan * in plotOptimResultsPan when errors were greater than 99.9% color were white (instead of red) * c simulator bug fix: at time 0, node that are inhibited and measured were reset to 0 but inhibitors are off. Fix is simple: do not reset inhibitors where time is zero * Fixing issue with time 0 not being simulated properly (see This fixes regression bug following fix made in release 1.11.3 * node name in the sif file containing the word AND (e.g. ligand) will not result in an AND-node anymore * Fixing issues with matrix subsetting, when the subsetting converts the matrix to a vector * plotOptimResultsPan: in the computation of root-mean-square error(for coloring the background), the NA data is not counted in the number of data points

  • CHANGES * Bioconductor’s version of the package got merged with the Github’s version leading to minor changes * readSIF reads only the unique interactions/lines from the SIF file * plotOptimResultsPan and plotCNOlist plots intermediate cue values (0,1) for CNORode add-on

  • NEW FEATURES * add readErrors and writeErrors functions in CNOlist: read/write measurement error/variance from/to MIDAS files * toSBML() function writes the model to SBMLqual format * makeCNOlist() can import MIDAS with multiple, continuous cue levels * add new function called crossInhibitedData


Changes in version 2.32.0:


  • SDFDataTable function, allows viewing compound image and data in a web browser.

  • read.SDFset can now skip over compounds with syntax errors in sdf files.

  • The functions ‘getIds’, ‘searchString’, and ‘searchSim’ have been modified to query pubchem directly rather than going through the intermediate web service ‘ChemmineTools’.


Changes in version 1.5.6:


  • The interface for working with chimeraviz has changed to comply with chimeraviz is the same as before, but methods have new names.

Changes in version 1.5.1:


  • Added support for the mm10 genome.


Changes in version 3.6:


  • Data pre-processing Function

  • rtracklayer import support


Changes in version 2.4.0:


  • A new function, peaks2genes(), to run the analysis up to, but not including, the enrichment testing. Useful for checking QC plots, check qualities of peak-to-gene assignments, and easier custom tests.


  • The hybridenrich() method now returns the same format as chipenrich() and polyenrich()


  • Vignette now describes all available gene sets


  • Fixed multiAssign weighting method to use the correct weights.


Version: 1.3.1 Text:

Version: 1.3.2 Text:


Changes in version 3.13.19:

  • Fix the bug in assignChromosomeRegion for the percentage calculation when nucleotideLevel equal to true.

Changes in version 3.13.18:

  • Fix the bug in assignChromosomeRegion for resetting seqlevels.

Changes in version 3.13.17:

  • Fix the bug in annoScore by setting the ignore.strand for punion.

Changes in version 3.13.16:

  • Fix the bug in assignChromosomeRegion for the integer overflow.

Changes in version 3.13.14:

  • Fix the warnings under windows.

Changes in version 3.13.12:

  • Change “class” function to “is” function.

Changes in version 3.13.11:

  • Fix the help file for assignChromosomeRegion.

Changes in version 3.13.10:

  • Improve binOverRegions.

Changes in version 3.13.9:

  • Improve addMetadata.

Changes in version 3.13.8:

  • Fix the warnings under windows.

Changes in version 3.13.6:

  • Improve the functions featureAlignedSignal and featureAlignedExtendSignal

Changes in version 3.13.5:

  • add minFragmentSize parameter to estFragmentLength

Changes in version 3.13.4:

  • suppress the message from featureAlignedExtendSignal

  • modified help files to make the samples run on local test.

Changes in version 3.13.3:

  • fix the bug in binOverRegions and binOverGene

Changes in version 3.13.2:

  • featureAlignedSignal generate outputs with rownames

Changes in version 3.13.1:

  • change the test value from GNAI3;MIR197 to GNAI3 to avoid the error because of update of annotation database.


Changes in version 1.15.2:

  • bug fixed for ‘overlap = “all”’ to consider strand information <2017-12-12, Tue>

Changes in version 1.15.1:

  • define downstream distance via options(ChIPseeker.downstreamDistance = 3000) +


Changes in version 1.5.1:


  • New column ‘maxPostInPeak’ containing the maximum posterior within each peak.

  • Score in exported BED files is calculated as -10*log10(maxPostInPeak).

  • ‘changeFDR()’ was renamed to ‘changeMaxPostCutoff()’.


Changes in version 2.0.0:

  • Broad support for DataFrame and MultiAssayExperiment data sets by feature selection and classification functions.

  • The majority of processing is now done in the DataFrame method for functions that implement methods for multiple kinds of inputs.

  • Elastic net GLM classifier and multinomial logistic regression classifier wrapper functions.

  • Plotting functions have a new default style using a white background with black axes.

  • Vignette simplified and uses a new mass cytometry dataset with clearer differences between classes to demonstrate classification and its performance evaluation.


Changes in version 1.99.4 (2018-04-19):


  • Added support for hdf5 files stored in assay slot via the HDF5Array package

  • Removed most defaults from RSEC arguments – pull them from underlying functions’ defaults.

Changes in version 1.99.3 (2018-04-17):


  • Re-implemented subsampleClustering() and combineMany() to use C++.

  • Method “adjP” in mergeClusters now allows for further requirement that gene have a minimal log-fold change (‘logFCcutoff’).


  • Fix bug in setBreaks (isPositive and isNegative variables)

  • use stringr::str_sort to make sort of character values locale independent

Changes in version 1.99.2 (2018-03-22):


  • Fix defaultNDims so that returns minimum of 50 and the minimum dimension of data.

  • Fix RSEC so still returns results if hit error after clusterMany.

Changes in version 1.99.0 (2018-02-15):


  • MAJOR CHANGE TO DEFINITION OF CLASS: This version consists of a major update of how dimensionality reduction and filtering is done. The class has been updated to extend the new SingleCellExperiment class, which save the dimensionality reductions. Furthermore, calculating of per-gene statistics, which are usually used for filtering, are stored in colData of the object and can be easily accessed and used for repeated filtering without recalculating. This has created a massive change under-the-hood in functions that allow dimensionality reduction and filtering. Changes to function names are the following: - transform is now transformData - New functions makeReducedDims and makeFilterStats will calculate (and thus store) dimensionality reductions and statistics for filtering the data. - New function filterData will return the filtered data as a matrix - New functions listBuiltInReducedDims and listBuiltInFilterStats give the list of currently available functions for dimensionality reduction and filtering statistics, respectively. - Filtering on arbitrary statistics and user-defined dimensionality reduction can used in clusterMany and related functions, so long as they are saved in the appropriate slots of the object.

  • Changed the following functions/arguments to be consistent with SingleCellExperiment naming conventions and improve distinction between terminology of cluster and clustering. - Capitalized constructor functions. Now: ClusterFunction() and ClusterExperiment() - nPCADims now changed to nReducedDims in clusterMany-related functions - nVarDims now changed to nFilterDims in clusterMany-related functions - dimReduce argument now changed to reduceMethod across functions - ndims to nDims in clusterSingle and makeDendrogram to keep consistency. - plotDimReduce to plotReducedDims - Changed nClusters to nClusterings to better indicate purpose of function. nClusters now gives the number of clusters per clustering. - addClusters to addClusterings and removeClusters to removeClusterings. New function removeClusters allows the user to actually ``remove” a cluster or clusters from a clustering by assigning samples in those clusters to -1 value. - clusterInfo() to clusteringInfo()

  • In addition these structural changes, the following enhancements are also included in this release - New function plotClusterLegend that will plot a legend for a clustering. - Color definition changes: showBigPalette has been replaced with showPalette and now can show any palette of colors. Adjusted color definitions of seqPal2 and seqPal4 to be completely symmetric around center. The colors in bigPalette have been changed and shuffled to reduce similar colors and massivePalette has been created by adding all of the non-grey colors (in random order) from colors() so that plotClusters will not run out of colors. - getClusterManyParams: now uses saved clusterInfo rather than more fragile clusterLabels to get parameters. The resulting output is formatted somewhat differently. - ClusterExperiment: removed transformation as a required argument. Now sets with default of function(x){x}. Allows argument clusterLegend to define the clusterLegend slot in the constructor.

    • plotClustersWorkflow: Argument existingColors in now takes arguments ignore,all,highlightOnly similar to plotClusters - plotDendrogram: Argument nodeColors now available. Changed defaults so default is to do colorblock of samples. - plotContrastHeatmap: Argument contrastColors now available to assign colors to the contrasts. Genes are now ordered by fold-change within each contrast. - plotClusters: argument existingColors now allows for the option firstOnly - makeDendrogram: now allows option ‘coCluster’ to the argument reduceMethod indicating use of the coClustering matrix to build the dendrogram. makeDendrogram now also has a method for building a dendrogram from an arbitrary distance function - clusterMatrix: now returns cluster matrix with rownames corresponding to sample names. - convertClusterLegend: now takes argument whichClusters


  • converted automatic assignment of colors in clusterLegend to be based on massivePalette so won’t run out on toy examples.

  • fixed minor bugs in plotHeatmap so that will - handle factor with only one value in annotation - will plot annotation labels when there is NA in the annotation - no longer calls internal function NMF:::vplayout in making those labels, more robust

  • fixed bug in how plotClustersWorkflow handled existing colors.

  • Fixed so diss now passed to subsampling in calls to clusterSingle/clusterMany

  • Fixed so plotClusters now will not give incomprehensible error if given duplicates of a color

  • Fixed plotDendrogram so will not create blank plot.


Changes in version 1.7.3:

  • Adding warn argument to pcp. Mostly for internal use. Fixes the warning with non default df argument repeating each perumtation.

  • Minor plotting improvments including providing a fix for the plot margin error.

Changes in version 1.7.2:

  • Tidying and fixing bugs in README. README now from README.Rmd to avoid similar problems in the future.

  • Adding codecov badge to Readme

Changes in version 1.7.1:

  • Updating author info and package URL.


Changes in version 3.5:


  • Add function orgKEGGIds2EntrezIDs to fetch the mapping between KEGG IDs and Entrez IDs

  • Add function makeAxtTracks

  • Add function addAncestorGO


Changes in version 1.11.0:

  • Add Shiny GUI


Changes in version 1.11.5 (2018-04-11):

  • Update vignettes

Changes in version 1.11.4 (2018-03-28):

  • Update examples in manual because change of functions

  • Put some functions obselete because change of database (such as COSMIC, regulatory segment ENSEMBL, ISCA)

  • remove R package, ggplot2, ggbio and trackviewer

Changes in version 1.11.3 (2018-02-25):

  • Update vignette because of the update of BiocStyle

  • Update two data (chipTFtrack.rda and genesGencodetrack.rda) because error formating

Changes in version 1.11.1 (2017-07-27):

  • Update vignette because of the update of BiocStyle

  • Add examples data that was not uploaded correctly the first time


Changes in version 1.17.1:

  • Legend(): add by_row argument to control the arrangement of legends if they are put in more than one columns

  • Legend(): use textGrob() if the point symbol is text

  • grid.dendrogram(): fix a bug that the dendrogram is wrong when row/column names have duplicated names.

  • anno_boxplot(): axis rescaled when outline = FALSE

  • oncoPrint(): rows are first ordered by total number of mutations and then ordered by number of samples that have mutations

  • correctly reorder rows

  • add row_gap argument for list of heatmaps

  • oncoPrint(): add j and i as optional argument for alter_fun


Changes in version 1.6.1:

  • Release Deprecated the cg_topics() and FitGoMpool() functions. Modified the FitGoM() function so that it has the flexibility to run multiple runs using the num_trials argument and also returns the BIC for each model fit. Modified the compGoM() function so that it can take either a topic model object, as well as a list of topic model objects. Also deprecated the base R graphics for the Structureplot and modified the StructureGGplot() function to take single label samples.

Changes in version 1.5.1:

  • Release We have added a FitGoMpool() function that automatically performs GoM model with multiple starting points and outputs the one run with the most optimal BIC. Besides, removed switch_axis_position() as a dependency from cowplot as the function has been deprecated.


Changes in version 1.7.12:

  • Change CrisprSe$insertion_sites “idxs” column to read indices for reads with multiple insertions

Changes in version 1.7.10:

  • CrisprSet method setCigarLabels now allows renaming labels

Changes in version 1.7.9:

  • Updates mergeCrisprSets in accordance with new order of counting operations

Changes in version 1.7.7:

  • Adds min and max for guide bounding box in plot

  • Fixes bug in plotFreqHeatmap caused when using “group” with a single row count matrix

Changes in version 1.7.5:

  • Update tests after changes to allele counting

  • Added create.plot argument for plotFreqHeatmap with signature CrisprSet.

  • Adds an option “style” to plotAlignments for colouring only mismatch nucleotides

  • Changes to narrowAlignments for PacBio cigar format

  • Bug fix in collapsePairs. Only occurred when running outside of readsToTarget.

  • Adds “alleles” accessor for relating variant labels to the truncated cigar strings

  • Return unmergeable alignments instead of raising an error

  • Minor code changes to make it easier to run a non-standard counting pipeline

  • Code from initialisers split into separate files for easier readability

Changes in version 1.7.4:

  • Added create.plot argument for plotFreqHeatmap with signature CrisprSet.

Changes in version 1.7.2:

  • Allowing plotting arbitrarily many subsets of aligned regions

Changes in version 1.7.1:

  • Reorganising plotAlignments code for allowing plotting subsets of the aligned regions.

  • Minor change to transcript plot plotVariants to make background white not transparent.


Changes in version 1.13.1:

  • Fully removed support for paramList objects.

  • Removed support for normalize(), modified default option for se.out= in normOffsert().


Changes in version 1.3.1:

  • Bug fix to interpreSpheres() when making additional plots.

  • Switched to custom colour calculation in plotCellIntensity().


Changes in version 1.11.3 (2018-01-19):


  • Added select all buttons to other marker related plots

  • Changed scaling and centering options to drop-down menus

  • Updated maintainer emails

  • Added transparency option to expression level plot points so points dont obscure each other too much. Point size can be adjusted to improve visibility as well


  • Fixed handling of global scaling so that expression values don’t fall outside the limits for the colour palette in the shiny color plots

  • Improved the outlier removal code in color plots to be more robust for various marker expression patterns

  • Shifted a line that compares fixedNum argument against the number of events so that it doesn’t break when the ‘min’ mergeMethod sets fixedNum to NULL

Changes in version 1.11.2 (2017-12-15):


  • Marker selection changed to selectize style, choices “All Markers” and “All Markers (scaled)” removed.

  • Added checkbox option to scale the legend and dot colours locally/globally

  • Added checkbox option to scale and center expression values

  • Added actionButton to select all markers (will update selectize choices to select all)

  • Added actionButton to update plot after changing marker selection (otherwise will update with each marker added/removed)


  • Changed limits of scatterplot scale from min-max to min-98th percentile to account for rare extreme outliers.

Changes in version 1.11.1 (2017-11-06):


  • Added a select/deselect all checkbox to the sample selection panel for ease of selection.

  • Added FlowSOM option and options to specify k for FlowSOM and Rphenograph in cytofkit_GUI.

  • Added a popup dialog to cytofkit_GUI that warns if more than 10,000 cells are being run with DensVM or isomap


  • Switched the treetype used for nn2 from bd to kd, as bd was causing problems in Phenograph clustering.


Changes in version 1.7.8:


  • nbases has replaced the nreads parameter in the learnErrors function. As suggested by the name, this controls the amount of data the machine learning uses by the total number of bases rather than the read count, which is more appropriate given the range of read-lengths in target applications.

  • OMEGA_C has been set to 1e-40 by default. This means that error-correction is no longer performed on all reads, but instead just those a post-hoc probability less than OMEGA_C=1e-40. In practice this has a very small impact on final abundances.


  • The memory usage and speed of assignSpecies on large datasets has significantly improved.

Changes in version 1.7.7:


  • Error-correction can now be modified, and turned off, by the OMEGA_C parameter, which controls the threshold at which reads that are inferred to contain errors are corrected (or not) to the sequence from which they are inferred to originate.


  • The DADA2 options enabling the quick gapless alignment check, and extremely conservative greediness in the partioning method were turned on by default (GAPLESS=TRUE, GREEDY=TRUE). Some speedup in the core denoising algorithm.

  • plotQualityProfile now includes a cumulative description of read length variation.

Changes in version 1.7.6:


  • A new and extremely conservative form of greediness in the core denoising algorithm was added, and can be turned on by setting the DADA2 option GREEDY=TRUE. This provides some speedup in the core denoising algorithm.

Changes in version 1.7.5:


  • The dada(…) function now accepts a list of “priors”, i.e. sequences for which there is prior evidence they might be real. Input sequences that match one of the priors are evaluated against a relaxed threshold of statistical evidence (OMEGA_P instead of OMEGA_A), and can be detected even as singletons.

  • The dada(…) function can perform “pseudo-pooling” with dada(…, pool=”pseudo”). In pseudo-pooling, the input samples are denoised independently, then a set of sequences that appear in at least MIN_PREVALENCE samples are used as priors for a second and final round of sample inference. MIN_PREVALENCE=2 by default.

Changes in version 1.7.4:


  • A new fast screen for optimal gapless alignments in the core denoising algorithm was added, and can be turned on by setting the DADA2 option GAPLESS=TRUE. This provides some speedup in the core denoising algorithm.

Changes in version 1.7.3:


  • Fixed an overflow bug on sequences 260nts or longer in the SSE=2 code.

Changes in version 1.7.2:


  • The DADA2 option enabling explicit 8-bit SSE vectorization in the C code was turned on by default (SSE=2). Some speedup in the core denoising algorithm.

Changes in version 1.7.1:


  • seqComplexity calculates the complexity of input sequences, and can be used to identify and filter out low-complexity sequences.


  • The default minOverlap parameter of mergePairs was reduced from 20 to 12, and the alignment parameters used during merging were altered to more strongly penalize mismatches and gaps, which improves merging performance in repetitive sequences.

Changes in version 1.17.2:

  • Fix the bug for formatSequence.R when seq is not character.

Changes in version 1.17.1:

  • add .globals environment.


Changes in version 1.3.7:

  • DaMiRseq performs multi-class classification anlysis.

  • The Stacking meta-learner can be composed by the user, setting the new parameter ‘cl_type’ of the DaMiR.EnsembleLearning() function. Any combination of the 8 classifiers is now allowed.

  • If the dataset is imbalanced, a ‘Down-Sampling’ strategy is automatically applied.

  • The DaMiR.FSelect() function has the new argument, called ‘nPlsIter’, which allows the user to have a more robust features set. In fact, several feature sets are generated by the bve_pls() fuction (embedded in DaMiR.FSelect()), setting ‘nPLSIter’ parameter greater than 1. Finally, an intersection among all the feature sets is performed to return those features which constantly occur in all runs. However, by default, ‘nPlsIter = 1’.

  • DaMiR.Allplot() accepts also ‘matrix’ objects as well as NA values (which are not plotted).

  • The DaMiR.normalization() function estimates the dispersion, through the parameter ‘nFitType’; as in DESeq2 package, the argument can be ‘parametric’ (default), ‘local’ and ‘mean’.

  • In the DaMiR.normalization() function, the gene filtering is desabled if ‘minCount = 0’.

  • In the DaMiR.EnsembleLearning() function, the method for implementing the Logistic Regression has been changed to allow multi-class comparisons; instead of the native ‘lm’ function, ‘bayesglm’ method implemented in the caret ‘train’ function, properly set, is now used.

  • The new parameter ‘second.var’ of the DaMiR.SV() function, allows the user to take into account a secondary variable of interest (factorial or numerical) that the user does not wish to correct for, during the sv identification.


Changes in version 1.11.15:

  • See changes in version 1.11.13 of the package Prostar


Version: 0.99.0 Text:


Changes in version 1.6.6:

  • HTML Header fixed

  • A more generic file import tool that senses string columns developed


Changes in version 0.20.0:


  • The decontam R package is released! Read more in our preprint:


Version: 1.4.1 Text:


Changes in version 1.99.3 (2013-07-25):


  • A few changes to shearwater vignette

  • Renamed arguments pi.gene and pi.backgr in makePrior()


  • Fixed bug in bf2Vcf() when no variant is called

Changes in version 1.99.2 (2013-07-11):


  • Updated CITATION

  • Added verbose option to bam2R to suppress output

  • Changed mode() to “integer” for value of loadAllData()


  • Fixed bug when only one variant is called in bf2Vcf()

Changes in version 1.99.1 (2013-06-25):


  • Using knitr for prettier vignettes

  • Including shearwater vignette


  • fixed issues with deletions in bf2Vcf()

  • makePrior() adds background on all sites

Changes in version 1.99.0 (2013-04-30):


  • New shearwater algorithm

  • Including VCF output through summary(deepSNV, value=”VCF”)


Changes in version 1.8.0:


  • Preserve rownames in gene annotation when converting between ‘DGEList’ and ‘DESeqDataSet’


Version: 1.15.4 Text: 2017-03-27 Lorena Pantano Fix: Fix typo in variable inside degClean Fix: Remove all columsn with NA values in degClean Feature: Plot only when degPatterns has only one gene. Thanks Amir Jassim. Feature: Add geom_cor to plot correlation values to a ggplot2 plot. Feature: Add eachStep option to degPattern to apply groupDifference to each time point and not only to the maximum and minimum values. Feature: Add covariates dendograme to degCovariates. Fix: Wrong matrix in degPattern. Thanks Amir Jassim. Feature: Add option to filter genes in degPattern. Thanks Amir Jassim. Feature: Return raw and summarise table in degPattern Feature: Migrate to rmarkdown for vignette Feature: Return prcomp output when using degPCA Fix: Typo in degPattern function, and set up to FALSE the use of consensusCluster. Fix: degPlot to be able to work with one gene. Feature: Add the option to look for specific patterns, or genes as reference. Feature: Return scaled values if scale==TRUE in degPattern. Feature: Add values used in plots for degPattern function. Thanks to Amir Jassim. Feature: Get significants for a list of DEGSet objects binding the tables first, calculating a new FDR, and aplying the filter as last step.

Version: 1.15.2 Text: 2017-01-08 Lorena Pantano Feature: Add support to list for significant and recover full table. Feature: Add support to different shrinkage estimator. Fix: Volcano plot was plotting wrong the shadows in the y-axis. Fix: Use correct option in DESeq2::results to count UP/DOWN genes. Feature: Allow to ask for up/down genes. Thanks to Radhika Khetani.

Version: 1.15.1 Text: 2017-11-13 Lorena Pantano Fix: Add checking point in degPCA Feature: Add function to plot basic expression signatures.


Changes in version 1.1.5:

  • Enabled differential testing with missing values.

  • Added data.frame output functionality from plotting functions.

  • Enabled multi-SE plotting in plot_normalization() and plot_imputation().

  • Deprecated se2msn() and msn2se() functions. Use as(‘MSnSet’) or as(‘SummarizedExperiment’) from MSnbase package instead.

  • Added a vignette on missing value handling in DEP.

  • Added citation: Zhang, Smits, van Tilburg et al. Nature Protocols 2018.


Changes in version 1.13.8:


  • Fixed a unit test that was breaking version 1.13.7.

Changes in version 1.13.1:


  • Added an extra example to regionMatrix() in response to


Changes in version 1.13.5:


  • Fixed an issue in plotCluster() on how it was loading the hg19IdeogramCyto object from the biovizBase package.

Changes in version 1.13.4:


  • Fixed an issue with a call to GenomicRanges::gaps() that affected how the introns were plotting in plotRegionCoverage() when the underlying data has a specifying start and end of the chromosome (that is, a seqinfo() with seqlengths specified). Thanks to Emily Burke for reporting this issue


Changes in version 1.20.0:

  • Added ‘lfcThreshold’ argument to lfcShrink() for use with type=”normal” and type=”apeglm”. For the latter, lfcShrink() will compute FSOS s-values, for bounding when the LFC will be “false sign or small”, where small is defined by lfcThreshold.

  • Switching to a ~10x faster apeglm implementation for use in the lfcShrink() function.

  • Beginning the deprecation of exploratory analysis of designs without replicates. Analysis of designs without replicates will be removed in the Oct 2018 release: DESeq2 v1.22.0, after which DESeq2 will give an error.

  • Elevate ‘minmu’ to DESeq() as this proves useful for single cell applications and certain zero-inflated data.

  • Elevate ‘useT’ to DESeq(), which will use (n - p) for the degrees of freedom of the t distribution, and if weights are provided, it will use the sum of weights as ‘n’.


Changes in version 0.99.12:

  • Documentation improvements.

Changes in version 0.99.9:

  • Add Parallelization.

Changes in version 0.99.0:

  • Package released.


Changes in version 2.8.0:

  • Features * add precision option to * dba.plot*: make plots use same precision as reports when thresholding
    • dba: add dir option to dba
  • Documentation updates * Vignette: change default to bFullLibrarySize=TRUE in description of DESeq2 analysis * Vignette: update vignette to not change dir * clean up description of bCalled in man page * modify example inman page to be clearer * dba: update man page to not change dir * dontrun example code for writing into LIB * dba: dontrun example code for dba setting wd to LIB

  • Bug fixes * Sort report by FDR instead of p_value * dba.peakset: fix bug when adding consensus peaks with chromosomes not present in some peaksets * dba.count: fix bug when recentering passed-in peaks * fix bug when using filtering from dba.analyze * dba.count: fix bug when passing in peaks using factors
    • dba.count: fix bug caused by not registering one of the C routines correctly.


Changes in version 0.99.2:


  • example data exprs.1 and exprs.2 are represented as matrices


  • this package imports rather than depends on the following packages: stats, DiffCorr, psych, igraph, BiocGenerics

  • messages are generated using message() instead of print() function.

  • use is() function to test inheritance relationships between an object and a class.

  • format NEWS file so that utils::news() parses the file.

Changes in version 0.99.1:


  • diffcoexp(), coexpr(), and comparecor() accept SummarizedExperiment objects.

Changes in version 0.99.0:


  • this package was given version number 0.99.0 and submitted to Bioconductor.


Version: 1.0.0 Text:


Changes in version 1.11.8:

  • Extended prunePairs() to acknowledge restrict, discard and cap in param= argument.

  • Extended getPairs() to acknowledge restrict, discard and cap in param= argument.

  • Added restrict.regions= option to connectCounts(), squareCounts().

  • Removed unnecessary normalize() export.

  • Upgraded, to run on Python 3 and to use Bio.SeqIO.parse().


Changes in version 1.0.0:

  • Five diffusion kernels available, they can be computed from an ‘igraph’ object.

  • Diffusion implementations divided between ‘diffuse_raw’ for deterministic scores and ‘diffuse_mc’ for permutation analysis, which is parallelised. In total, seven diffusion scores are accessible through the ‘diffuse’ function.

  • Performance evaluation wrapped in the ‘perf’ function.

  • Helper functions in helpers.R (to plot diffusion scores, to check if a kernel matrix is actually a kernel, to extract largest CC from a graph)


Version: 1.11.1 Text: Added functions detect DMRs from biological replicates (beta regression) Added functions to compute/plot spatial correlation of methylation level Added function to extract GC content (useful for NOME-seq)


Changes in version 0.99.11 (2018-04-05):

  • dmrseq now provides support for detecting large-scale methylation blocks. To use this feature, specify block=TRUE, and increase the smoothing span parameters minInSpan, bpSpan, and maxGapSmooth. More details are provided in the documentation and vignette.

Changes in version 0.99.8 (2018-03-21):

  • dmrseq no longer requires balanced, two-group comparisons. To run using a continuous or categorial covariate with more than two groups, simply pass in the name of a column in pData that contains this covariate. A continuous covariate is assmued if the data type in the testCovariate slot is continuous, with the exception of if there are only two unique values (then a two group comparison is carried out).

Changes in version 0.99.6 (2018-03-02):

  • dmrseq is now available on Bioconductor devel (3.7) !


Changes in version 0.99.5:


  • add code to fail gracefully if uniprot is down

Changes in version 0.99.4:


  • add code to fail gracefully if ensembl is down

Changes in version 0.99.3:


  • add Citation of publication

Changes in version 0.99.2:


  • address comments from Bioconductor review

Changes in version 0.99.1:


  • new functions import_vcf.R and import_txdb.R to use standard Bioconductor classes

  • minor other updates

Changes in version 0.99.0:


  • First Version of DominoEffect submitted to Bioconductor


Changes in version 3.5.2:

  • bug fixed of gseaScores <2018-04-18, Wed> +

  • mv web site to


Version: 0.99.10 Category: ARGUEMENT Text: show.legend added as argument to allow the option to show or not show the legend as per ggplot2.

Version: 0.99.9 Category: FEATURES Text: New function called draw_recept_dom(). This function allows the drawing of the TOPO_DOM and TRANSMEM types of receptors. Data from TNFR1 and CD40 are included to demonstate the function.

Version: 0.99.8 Category: FEATURES Text: New function called extact_transcripts. This function will ammend the data frame to allow each chain from the same UniProt accession number to to drawn separately. A vignette entitled drawProteins_extract_transcripts has been written to demonstrate.

Version: 0.99.8 Category: FEATURES Text: LazyData is now false and NAMESPACE updated as per Bioconductor review.

Version: 0.98.3 Category: FEATURES Text: New function called draw_canvas. This function was previously within draw_chains but has now been pulled out to allow the generation of a canvas separately from the chains. It did require quite a rewrite but I think it will make things more useful For example, it will allow the plotting of domains without chains which has the potential to be very useful.

Version: 0.98.2 Category: FEATURES Text: Rename functions from geom to draw. E.g geom_chains is now geom_draw. This is because they weren’t really geoms and using the word draw seem more helpful and a better reflection of the function.

Version: 0.98.2 Category: LAUNCH VERSION 0.98.1 Text:

Version: 0.98.2 Category: FEATURES Text: Drawing protein schematics from Uniprot database with Accession numbers


Changes in version 0.99.0:

  • New package DropletUtils, for handling droplet-based single-cell RNA sequencing data.


Changes in version 2.15.5:

  • Ensured that counting happens in a strand specific way when stranded data is provided

  • The easyRNASeq and all related methods are now defunct.

  • Added a BamParam strandProtocol argument value to count reads on the reverse strand

  • Removed calls to RangedData constructor defunct parameters in unit tests

  • Removed dependencies to RnaSeqTutorial in unit tests

  • Removed the easyRNASeq vignette. Replaced it with a knitr vignette - to be completed.

Changes in version 2.15.4:

  • Removed dependencies to RnaSeqTutorial

  • Removed calls to RangedData constructor defunct parameters


Changes in version 4.22.0:


  • fixed compilation errors on Solaris


Changes in version 3.22.0:

  • New function read10X() to read 10X Genomics files.

  • New function nearestTSS() to find the nearest transcriptional start site (TSS) for given genomic loci.

  • New function nearestReftoX() to find the element of a reference table that is closest to each element of an incoming vector.

  • New function modelMatrixMeth() to construct design matrices for analysis of methylation data.

  • New function filterByExpr() to filter low expression genes or features.

  • New rowsum method for DGEList objects.

  • nbinomUnitDeviance() now respects vectors.

  • DGEList() takes ‘group’ from ‘samples’ only if samples has a column called group.

  • decideTestsDGE() now includes a ‘label’ attribute, which allows more information row.names for the summary results table from decideTestsDGE() or decideTests().

  • Design now defaults to y$design for all the gene set tests.

  • More intuitive error messages from glmFit() when the arguments are not conformal.

  • Update User’s Guide to cite the Chen et al (2017) methylation workflow.

  • Change glmTreat() default to lfc=log2(1.2).

  • Fix incorrect implementation of weights in adjustedProfileLik().

  • Bug fix to glmLRT() when there is just one gene but multiple contrasts.

  • Bug fix to cpmByGroup().


Changes in version 1.6.1 (2017-12-03):

  • added: exception handling code to avoid generateReport failure when generating GO graphs under some circumstances.

  • fixed: a minor issue in writing CSV files.


Changes in version 1.9.3:

  • support visualize category signals

  • add discretize() to transform continuous matrices to discrete matrices

  • add one more vignette showing the usage of categorical signals

Changes in version 1.9.2:

  • improvement on vignettes

  • enriched_scores() directly applied to the normalized matrix

  • row dendrogram is reordered by enriched scores if cluster_row is set to TRUE


Changes in version 2.10.0:

  • Adding scripts to inst/scripts to invoke the EnrichmentBrowser from the command line (for non-R users)

  • GRN compilation: supporting additional pathway databases (via graphite)

  • Caching for download of GO and KEGG gene sets (via BiocFileCache)

  • Default output destination changed to rappdirs::user_data_dir(“EnrichmentBrowser”)

  • Function names: deprecation of x.x notation - read.eset -> readSE - probe.2.gene.eset -> probe2gene - de.ana -> deAna - compile.grn.from.kegg -> compileGRN - ggea.graph -> ggeaGraph - -> makeExampleData


Changes in version 2.3.14:

  • New ProteinDomainSourceFilter and ProteinDomainIdFilter.

Changes in version 2.3.11:

  • Fix for issue #75.

Changes in version 2.3.9:

  • Add transcriptToCds and cdsToTranscript functions (issue #73).

Changes in version 2.3.8:

  • Fix problem creating EnsDb from GTF file lacking exon IDs (issue #72,

Changes in version 2.3.7:

  • Switch to EnsDb.Hsapiens.v86 in examples, unit tests and vignettes.

Changes in version 2.3.6:


  • Fix issue #69 failing to map genomic coordinates to proteins if different genomic coordinates are mapped to the same transcripts/proteins.

Changes in version 2.3.5:


  • Fix problem mapping genomic coordinates on named GRanges.

Changes in version 2.3.2:


  • Functionality to between genomic and transcript-relative or protein-relative coordinates: proteinToTranscript, genomeToTranscript, transcriptToGenome, transcriptToProtein, genomeToProtein.

Changes in version 2.3.1:


  • Functionality to map within-protein coordinates to genomic coordinates: proteinToGenome function.


Changes in version 1.22.0:


  • add support for Ensembl release 92

  • add support for Ensembl release 91


  • The default ‘host’ is not specified, defaulting to vep default of ‘’. The default previously was ‘’ Users in the US may find connection and transfer speeds quicker using the East coast mirror, ‘’. It was updated because the mirror only supports current and current minus one vep version, and to bring the default in line with the default of vep.


Version: 2017.01 Category: Github made public and submitted to Bioconductor Text:


Changes in version 999.999:

  • This NEWS file is only a placeholder. The version 999.999 does not really exist. Please read the NEWS on Github: <URL:>


Changes in version 999.999:

  • This NEWS file is only a placeholder. The version 999.999 does not really exist. Please read the NEWS on Github: <URL:>


Changes in version 999.999:

  • This NEWS file is only a placeholder. The version 999.999 does not really exist. Please read the NEWS on Github: <URL:>


Changes in version 1.13.1:


  • replaced QuasiSeq with edgeR for differential expression testing, due to deprecation of QuasiSeq

  • users will observe significant speed increases for DE testing

  • users will observe changes in results from example data, Quasi-Likelihood methods are similar for edgeR and QuasiSeq, but not exactly identical, so P-value distributions are different, LODR estimates have changed.

  • dispersion plot (dispPlot) is now generated via edgeR instead of QuasiSeq, using a similar Quasi-Likelihood dispersion shrinkage method.


  • changed behavior so that dispPlot is not deleted if DE testing is rerun, instead increment file name to prevent overwriting.


Version: 1.2.0 Category: Publication Text:

Version: 1.2.0 Category: Wei, Zheng, et al. “esATAC: an easy-to-use systematic pipeline for ATAC-seq data analysis.” Bioinformatics (2018 Text:

Version: 1.2.0 Category: Text:

Version: 1.2.0 Category: Fix some known bugs Text:

Version: 1.2.0 Category: Speed up motif scanning Text:

Version: 2018.04.18 Category: Using the new method to scan motif in the genome, remove preset motif data. The new method Text:

Version: 2018.04.18 Category: is from package “motifmatchr”, it cost less than 2mins for a sample(test sample: SRR891268; Text:

Version: 2018.04.18 Category: of course, depend on your computer performance Text:


Changes in version 1.7.4:

  • Fix trait-related problem in binomial test.

Changes in version 1.7.3:

  • Deprecating the probability test because of problems with the gap package in MS Windows.


Changes in version 1.5.1:

  • Updated contact email.


Version: 0.99.6 Text: Small corrections in vignette

Version: 0.99.6 Text: Removed rm calls

Version: 0.99.5 Text: Small correction in vignette

Version: 0.99.5 Text: Version bump to see if bioc build is bugged

Version: 0.99.4 Text: Moved contents of to NEWS

Version: 0.99.4 Text: Deleted most of data-raw folder, moved the rest to inst/script

Version: 0.99.4 Text: Removed redundant Authors field in DESCRIPTION

Version: 0.99.4 Text: Removed class(data) != "FELLA.DATA" by using built-in is.FELLA.DATA

Version: 0.99.3 Text: Version bump (biomaRt down?)

Version: 0.99.2 Text: Fixed more doc links

Version: 0.99.1 Text: Fixed doc links (hopefully)

Version: 0.99.1 Text: Updated funding in vignette

Version: 0.99.1 Text: Travis will only test the devel branch

Version: 0.99.0 Text: Submission to Bioconductor


Changes in version 1.5.2:

  • fgsea throws warning for rank ties

  • fgsea throws warning for duplicate gene names

  • Leading edge is now ordered by decreasing of absolute statistic value

Changes in version 1.5.1:

  • Reproducibility fixes

  • Added collapsePathway function to intelligently collapse overlapping pathways

  • Added fgseaLabel function for label-permuting GSEA


Changes in version 1.14.0:


  • the engine for plotting the trajectories is now based on plotly, abandoning the older rgl-based solution


  • vignette: now also based on Rmarkdown, leaving the older Rnw-pdf be

  • shortened example lines for better documentation

  • better definition of import statements for better behaviour with other packages

  • updated travis.yml for current setup


Changes in version 1.5.6 (2018-03-08):

User Visible Changes

  • BUG FIX: the G2 peak of the B sample was not getting incorporated into model construction, which caused model fitting to fail on samples with histograms skewed towards the left.

  • Updated DebrisModel documentation.

Internal Changes

  • Fixed broken test.

Changes in version 1.5.3 (2018-01-17):

User Visible Changes

  • The browser interface will no longer allow users to enter arbitrary text to select the number of samples. Only valid values, i.e., 1, 2, or 3, will be offered as choices. The old version would crash with a bad value for sample number.

  • Improved file importing, so that low-quality samples for which peaks cannot be detected can still be imported.

  • Added a new argument to FlowHist, so users can set the threshold below which the data is ignored when screening out debris. The default remains the same, 40, but users with very clean histograms, with peaks far to the left, can now lower this value if needed.

  • Model fitting is now limited to the range of the data. That is, empty bins at the right (upper) end of the histogram will not be included when fitting the NLS. This addresses problems that generated inflated RCS values.

  • The limits for the linearity parameter have been extended from 1.9-2.1, to 1.5-2.5. This will improve/enable model fitting on samples where the linearity (the ratio of the G2/G1 peaks) was outside the range 1.9-2.1.

Changes in version 1.5.1 (2017-12-04):

Minor bug squashed

  • Changes made upstream to car::deltaMethod() introduced a bug. This will be resolved as of car version 2.1-7. Until that version of car makes it’s way into CRAN, calling deltaMethod() on an nls object will require the argument vcov. be explicitly set to vcov, a function in the stats package. This has been done in flowPloidy, and should be invisible to users. In addition, the bug is not present in the current R release, so it should not need to be backported to previous versions of flowPloidy.


Changes in version 2.28.2:

  • korg now include 5245 KEGG species. In addition an updated version of korg is now checked out from Pathview Web server by loading .rda file (inst4ead of read .tsv file) when needed.


Changes in version 0.99.0:

  • GARS package has been released!


Changes in version 0.99.11:

  • example(GDSArray) added.

Changes in version 0.99.10:

  • renamed “gdsNodes” method as “gdsnodes”.

Changes in version 0.99.7:

  • renamed “GDSlight” as “GDSFile”.

  • added accessors for “GDSFile”.

  • $ method check for valid gds node.

Changes in version 0.99.6:

  • GDSArray seed setter and getter.

Changes in version 0.99.5:

  • Implemented “GDSlight” class and $ method.

Changes in version 0.99.1:

  • Added example for GDSArray-methods.Rd.

  • Added BiocViews.


Changes in version 1.16.0:


  • a new storage name ‘single’ in add.gdsn() for single-precision floating numbers

  • improve the efficiency of bit2-unpacking when there are lots of zero

  • system.gds() outputs ‘POPCNT’ flag if available

  • enable the compression modes “LZMA.ultra”, “LZMA.ultra_max”, “LZMA_RA.ultra” and “LZMA_RA.ultra_max”

  • show more compression information in system.gds()


  • avoid the integer overflow when the compression rate is too small using LZMA_RA (e.g., <0.01%)

Changes in version 1.14.0-1.14.1:


  • tweak error messages in apply.gdsn()

  • cleanup.gds() allows a file name with a prefix ‘~’ which will be automatically replaced by the home directory


Changes in version 1.21.2:

  • Fix the problem for missing links in documentation.

Changes in version 1.21.1:

  • Fix the problem for missing links in documentation.


Changes in version 2.9.3:

  • New methods assocTestSingle and assocTestAggregate are refactors of assocTestMM and assocTestSeq/assocTestSeqWindow, respectively. assocTestSeq and assocTestSeqWindow are deprecated. assocTestMM is still used for GenotypeData objects, but will be deprecated in a future release. fitNullModel is a refactor of fitNullMM/fitNullReg and should be used with the new association test methods.


Version: 0.99.0 Category: Pre-BioC submission Text:

Version: 0.99.1 Category: Fixes for BioC submission Text: notNMD is not required for vignettes

Version: 0.99.1 Category: Fixes for BioC submission Text: whippet files are read in as a single object

Version: 0.99.1 Category: Fixes for BioC submission Text: Fixed bug where leafcutter set creation snowballed

Version: 0.99.2 Text: Fix for fread()’ing in gzip files on windows

Version: 0.99.4 Text: Exon skipping and intron retention now works with manual coordinates again

Version: 0.99.4 Text: Documentation updates


Version: 1.11.3 Category: IMPROVEMENTS AND BUG FIXES Text: fixed an error of data.table() function that occurs when GrangesList object contains unnamed windows

Version: 1.11.3 Category: in ScoreMatrixBin() function Text:

Version: 1.11.2 Category: IMPROVEMENTS AND BUG FIXES Text: improved the C++ function Median_c() to handle NAs

Version: 1.11.2 Category: IMPROVEMENTS AND BUG FIXES Text: the following C++ functions return NAs instead of zeros if the length of the vector is smaller than the number of bins: binMean(), binMedian(), binMax(), binMin(), binSum()

Version: 1.11.2 Category: NEW FUNCTIONS AND FEATURES Text:

Version: 1.11.2 Category: C++ functions that compute a desired value from a vector and handle NAs Text: Mean_c() - computes a mean value,

Version: 1.11.2 Category: C++ functions that compute a desired value from a vector and handle NAs Text: Max_c() - computes a maximum values,

Version: 1.11.2 Category: C++ functions that compute a desired value from a vector and handle NAs Text: Min_c() - computes a minumum values,

Version: 1.11.2 Category: C++ functions that compute a desired value from a vector and handle NAs Text: Sum_c() - computes a sum value.

Version: 1.11.1 Category: IMPROVEMENTS AND BUG FIXES Text: bug fix relating to ScorematrixBin that returns all 1’s when is.noCovNA=T (

Version: 1.11.1 Category: IMPROVEMENTS AND BUG FIXES Text: xcoords argument for heatMatrix and multiHeatMatrix now can take character vectors.

Version: 1.11.1 Category: The character vectors will label the x-axis of heatmaps. Examples: xcoords=c(“-2kb”,”0”,”2kb Text:


Changes in version 1.16.0:


  • Add coercion from list to GAlignmentsList.


  • Improve performance of [[<- on GAlignmentsList objects. This is a 100x speedup or more on a big GAlignmentsList object.


  • Remove spurious warning in summarizeOverlaps().


Changes in version 1.32.0:


  • The first argument of mapToTranscripts() and pmapToTranscripts() now can be a GPos object and a GPos object is returned in that case.

  • Add ‘use.names’ argument to “transcripts”, “exons”, “cds, and “promoters” methods for TxDb objects.

  • makeTxDbFromUCSC() now uses direct SQL queries (to the UCSC MySQL server at instead of rtracklayer::getTable() to fetch data from the Genome Browser. This avoids the issue reported here . Another benefit is that direct SQL queries are much faster than rtracklayer::getTable().


  • The GRanges object returned by mapToTranscripts() or pmapToTranscripts() takes the transcript lengths as seqlengths.

  • pmapToTranscripts() always takes the transcript name as the seqname, even when there is no overlap. Before, it used “UNMAPPED” as the seqname when there was no overlap.


  • Fix bug where ‘coverageByTranscript(x, transcripts)’ was erroring in situations where ‘transcripts’ contains transcripts with an exon that receives no coverage and is located on a sequence for which the seqlength is not available in ‘seqinfo(x)’ nor in ‘seqinfo(transcripts)’.


Changes in version 1.32.0:


  • 2 improvements to the “promoters” method for GenomicRanges objects: - The ‘upstream’ and ‘downstream’ arguments now can be integer vectors parallel to ‘x’, - The ‘use.names’ argument now is supported. This is for consistency with the other intra range transformations.


  • GenomicRanges now is a List subclass. This means that GRanges objects and their derivatives are now considered list-like objects (even though [[ don’t work on them yet, this will be implemented in Bioconductor 3.8).

  • Add the CompressedGRangesList class as a replacement for the GRangesList class. The long term goal is that GRangesList becomes a virtual class with CompressedGRangesList as a concrete subclass. Note that the GRangesList() constructor now returns a CompressedGRangesList instance instead of a GRangesList instance.

  • GenomicRangesList is now a virtual class (like IntegerRangesList is).

  • GRanges derivatives no longer support the ‘x[i, j] <- value’ form of subassignment. This feature was of very limited usefulness and no Bioconductor package was using it.

  • Improve performance of nearest(), precede(), and follow() on a GRanges object.

  • Improve performance of coverage() on a GPos object.

  • Improve performance of sort() on a GRangesList object. Also now it supports ‘ignore.strand’. See (and note how unnicely these changes were requested).

  • Improve performance and error handling of coercion from RleList to GRanges. This is a 50x speedup or more when the RleList object to coerce has thousands of list elements or more.


  • Fix coercion from RleList to GRanges when some list elements in the object to coerce have length 0 (see for original report by Xiaotong Yao).

  • Fix bug in nearest() when an unstranded range in ‘query’ precedes or follows more than one range in ‘subject’.


Changes in version 1.4.0:


  • The function ‘scores()’ has been deprecated and replaced by the function ‘gscores()’.

  • The argument ‘scores.only’ in the function ‘scores()’ has been deprecated and replaced by calling the function ‘score()’.

  • The ‘MafDb’ class has been deprecated and now the ‘GScores’ class supports former ‘MafDb’ objects. The ‘mafByOverlaps()’ and ‘mafById()’ functions have been deprecated and replaced by the function ‘gscores()’. The ‘populations()’ function from the ‘MafDb’ API has been integrated into the ‘GScores’ API.

  • Added metadata on genomic scores groups, available through the function ‘gscoresGroups()’, on availability of non-single nucleotide regions through the function ‘gscoresNonSNRs()’, and on the default population used through the function ‘defaultPopulation()’.

  • New AnnotationHub resources have been added during this release cycle: phyloP60way.UCSC.mm10, LINSIGHT, phastCons46wayPlacental, phastcons46wayPrimates.

  • Added a BiocSticker at

  • Added citation information after package publication has been accepted at Bioinformatics.


Changes in version 1.7 (2018-01-20):


  • Additional functions are added sporadically.

  • This news file reports changes that have been made as the package has been developed.


  • Bayesian inference using stan (rstan package)

  • Two bayesian inference methods to support both continuous and dichotomous phenotypes

  • Additional genotype-phenotype association metrics added

  • Posterior predictive checks implemented

  • Procedure for data reduction (runDiagnostics) added

  • Tutorial updated

  • Simple procedure for phylogenetic bias estimation implemented

  • Retrospective power analysis module

To do

  • Add practical examples where genphen has been used.

  • Implement modules for data augmentation

  • Update todo after data augmentation


Version: 2.47.1 Text: Bug fixes: * Fixes problems with intermittent connection issues (which were not intermittend connection problems, it seems)


Changes in version 1.11.3:

  • update msaplot to use DNAbin/AAbin internally and also compatible with treedata object <2017-12-14, Thu>

  • clean up code <2017-12-13, Thu>

  • remove paml_rst, codeml_mlc, codeml and jplace fortify methods according to the change of treeio (v = 1.3.3) <2017-12-07, Thu>

Changes in version 1.11.2:

  • keep tree order (previously using postorder) <2017-12-06-Wed> +

  • remove beast object support as read.beast output treedata object in treeio <2017-12-05, Tue>

  • deprecate subview, annotation_image and phylopic; remove theme_transparent <2017-12-04, Mon>

  • geom_tiplab now supports geom = “image” or geom = “phylopic” <2017-12-04, Mon>

  • A new layer geom_nodelab that equivalent to geom_tiplab but works for internal node <2017-12-04, Mon>

Changes in version 1.11.1:

  • bug fixed in geom_tiplab, now offset parameter works with align=TRUE. <2017-11-20, Mon>

  • enable mrsd parameter for treedata object <2017-11-15, Wed>

  • set_hilight_legend supports alpha parameter <2017-11-15, Wed> +


Changes in version 0.99.14:


  • allow for custom annotations (alternative to default Bioconductor annotation packages)

  • allow for custom ontology graph (alternative to default integrated GO-graph)

Changes in version 0.99.12:


  • update GO-graph (version 10-Apr-2018)


Version: 1.5.1 Text:


Changes in version 1.25.9 (2018-04-28):

  • Updated all pathway data.

Changes in version 1.25.7 (2018-04-18):

  • cytoscapePlot returns an handle to the exported graph.

Changes in version 1.25.6 (2018-04-11):

  • Parallel versions of clipper and topologyGSA methods.

Changes in version 1.25.3 (2018-03-23):

  • Faster conversion of identifiers.

Changes in version 1.25.2 (2018-03-23):

  • Documentation fixes.

  • Removed deprecated objects biocarta, humancyc, kegg, nci, panther, reactome.

Changes in version 1.25.1 (2017-12-13):

  • Export the pathwayURL function.


Changes in version 1.11.1:

  • Allow “karyotype” to be specified as a GRanges object.

  • Include Anshul Kundaje’s black lists for convenience.

  • Support merging of grey lists from multiple input files.


Changes in version 1.28:


  • Arguments ‘rnaseq’, ‘kernel’, ‘no.bootstraps’ and ‘bootstrap.percent’ have become defunct.

  • A Bioconductor sticker has been created and it is available at


Changes in version 1.13.3 (2018-01-10):

  • Updated README.

  • Updated vignettes.

Changes in version 1.13.2 (2017-12-10):

  • Minor changes.

Changes in version 1.13.1 (2017-11-20):

  • Updated CITATION FILE.

  • Updated documentation.

  • Added RcppArmadillo to improve performance.


Changes in version 1.16.0:

  • KIR information in hlaLociInfo()

  • new functions hlaGenoSubsetFlank() and hlaLDMatrix()


Changes in version 0.99.27 (2018-04-08):

  • Correcting Bionconductor style

Changes in version 0.99.9 (2018-03-09):

  • Adapting hipathia package to SummarizedExperiment and MultiAssayExperiment.

Changes in version 0.99.8 (2018-03-07):

  • First version using AnnotationHub to load annotation files.

Changes in version 0.99.7 (2018-02-14):

  • Last version supporting hpAnnot as annotation package


Changes in version 1.23.0:


  • Add use.names and header options in exportC


  • Fix bug in getExpectedCountsMean for non-symmetrical data

  • Deal with NA in getPearson function

  • Fix bug in normLGF leading to non symmetrical matrices


Changes in version 1.21.1:

  • use html_document (rather that deprecated html_document2) <2018-01-19 Fri>


Version: 1.19.3 Category: —- Fixed bug for the DESeqDataSet class when there are additional columns in the Text:

Version: 1.19.3 Category: colData of the object beyond those used in the design (thanks to Stephanie Durand Text:

Version: 1.19.3 Category: for finding the bug!) Text: – Keep rownames and colnames on filtered data for matrix and data.frame class


Changes in version 1.4.0:


  • Specified single go term selection for generating heatmaps of gene signatures

  • Added support for logFC shrinkage, following the latest devels of DESeq2


  • Corrected output for the vignette, as html_document2 is now deprecated

  • Menus are back in the expanded form

  • Fixed the behavior with addMLE


  • Added further progress indicators to give feedback during lengthy steps

  • Improved ggplotCounts for better scale display, using exact arg matching, defaulting to the transformed counts


Changes in version 1.11.4:

  • fix the warning for help files in windows

Changes in version 1.11.3:

  • add utr3.danRer10.

Changes in version 1.11.2:

  • fix the error by the change of GRanges.


Changes in version 0.99.1-4:

  • Package accepted in Bioconductor

  • Adjustment for R version 3.5

  • Minor fixes


Changes in version 1.4.0:


  • interest() and interest.sequential() functions now support “IntSpan” method, allows counting intron- spanning reads.

  • psi() function is added. It calculates Psi values.

  • annotateU12() fucntion supports DNAStringSet objects as its refGenome input.

  • Improved vignette document.


  • eBayesInterest() removed.


  • interest.sequential() and interest() corrections to their object output option.

  • annotateU12() modified to work correctly with the new changes in Biostrings package.


Changes in version 1.7.5:

  • added usage of clustering method FORK on unix-systems (thanks to Pablo Moreno)

  • fixed bug in parallelization to prevent conflicts with package ‘snow’

Changes in version 1.7.4:

  • preceded parallel-functions with ‘parallel::’ to use right package

  • fixed bug in function writeRScript using ‘loess’ retention time cor.

  • decreased runtime for R CMD check IPO

Changes in version 1.7.3:

  • added runnable examples

  • decreased size of pictures in vignettes/rsmDirectory

  • decreased runtime for unit-tests

  • replaces expand.grid with expand.grid.subset (in utils.R)

Changes in version 1.7.2:

  • bugfix: try to prevent error in calcPPS possibly caused by NAs

  • replaced cat() and print() calls with message()

Changes in version 1.7.1:

  • checking correlation of peak-shape with sinus curve (-pi/2 to pi*1.5), normal distribution or checkBorderIntensity

  • findIsotopes.IPO renamed parameter checkBorderIntensity to checkPeakShape

  • performance improvement calcPPS for checkPeakShape=FALSE

  • calculating xcmsSet-object and respective PPS for each DoE. (PPS is not estimated from rsm anymore)

  • additionally forwarding nSlaves for xcmsSet-function (also see getDefaultXcmsSetStartingParams())

Changes in version 1.7.0:

  • added support for XCMS-method retcor.loess

  • updated help files

  • changed return value of getRGTVValues

  • adapted unit tests

  • parameter scanrange for XCMS-methods findPeaks can be set but not optimized


Changes in version 2.14.0:


  • Add the windows() generic with various methods. This is a “parallel” version of window() for list-like objects i.e. it does ‘mendoapply(window, x, start, end, width)’ but uses a fast implementation. Also add heads() and tails() as convenience wrappers around windows(). They do ‘mendoapply(head, x, n)’ and ‘mendoapply(tail, x, n)’, respectively, but use a fast implementation. They’re replacements for S4Vectors::phead() and S4Vectors::ptail() which are now deprecated.

  • Add equisplit() to split a vector-like object into a specified number of partitions with equal (total) width. This is useful for instance to ensure balanced loading of workers in parallel evaluation.

  • promoters() arguments ‘upstream’ and ‘downstream’ now can be integer vectors parallel to ‘x’ (for consistency with the other intra range transformations).

  • The promoters() generic and methods get the ‘use.names’ argument.

  • Add “resize”, “flank”, and “restrict” methods for Views objects.

  • Add “as.integer” method for Pos objects (equivalent to pos()).


  • The Ranges virtual class is now the common parent of the IRanges, GRanges, and GAlignments classes (GRanges and GAlignments are defined in the GenomicRanges and GenomicAlignments packages, respectively). More precisely, Ranges is a virtual class that now serves as the parent class for any class that represents a vector of ranges. The ranges can be integer ranges (i.e. ranges on the space of integers) like in an IRanges object, or genomic ranges (i.e. ranges on a genome) like in a GRanges object. Note that because Ranges extends List, all Ranges derivatives are considered list-like objects. This means that GRanges objects and their derivatives are considered list-like objects, which is new (even though [[ don’t work on them yet, this will be implemented in Bioconductor 3.8).

  • Similarly the RangesList virtual class is now the common parent of the IRangesList, GRangesList, and GAlignmentsList classes.

  • IRanges objects don’t support [[, unlist(), as.list(), lapply(), and as.integer() anymore. This is a temporary situation only. These operations will be re-introduced in Bioconductor 3.8 but with a different semantic. The overall goal of all these changes is to bring more consitency between IRanges and GRanges objects (GRanges objects will also support [[, unlist(), as.list(), and lapply() in Bioconductor 3.8). Non-exported IRanges:::unlist_as_integer() helper is a temporary replacement for what unlist() and as.integer() used to do a IRanges object.

  • Move the pos() generic to BiocGenerics.

  • Switch order of breakInChunks() arguments ‘chunksize’ and ‘nchunk’ to be consistent with tileGenome().

  • tile() and slidingWindows() now preserve names.

  • Optimize [[<- on a CompressedList object. Was very inefficient. The optimized method can be up to 100x faster or more on a long object.

  • All the S4Vectors-specific material in the IRangesOverview.Rnw vignette has moved to the new S4VectorsOverview.Rnw vignette located in the S4Vectors package.


  • Deprecate the RangesList() constructor. IRangesList() should be used instead.

  • The “ranges” methods for Hits and HitsList objects are now defunct (were deprecated in BioC 3.6).

  • The “overlapsAny”, “subsetByOverlaps”, “coverage” and “range” methods for RangedData objects are now defunct (were deprecated in BioC 3.6).

  • The universe() getter and setter as well as the ‘universe’ argument of the RangesList(), IRangesList(), RleViewsList(), and RangedData() constructor functions are now defunct (were deprecated in BioC 3.6).


Changes in version 0.99.3:

  • Custom tours can be restarted via the dropdown menu button, overwriting the default tour

  • Added functionality to provide a custom title to be displayed in the app

  • Preserve data points and width ratio upon zoom on discrete variables

Changes in version 0.99.2:

  • Added functionality for providing additional custom tours, to be launched directly upon starting the app.

Changes in version 0.99.1:

  • Added grid-based visual point downsampling for faster plotting, including control of resolution.

  • Added button “Clear features” for heat maps.

  • Reorganized buttons in heat map panels.

  • Maintainer badge transferred to Federico

Changes in version 0.99.0:

  • Initial submission to Bioconductor.


Changes in version 3.6:


  • JASPAR2018 data package


Changes in version 0.99.0:

  • Pre-release of the package.


Changes in version 1.3.1:

  • Release

  • deprecated the two functions - logomaker and nlogomaker for standard and EDLogo. All logo plots can be now be generated using the same function - logomaker(). The type argument in this function can be chosen to be Logo or EDLogo.

  • trimmed the package down from nearly 60 exported functions to just 7 exported functions.

  • The format of the input data is now made more flexible - it allows for a vector of character sequences, along with the PFM or the PWM matrix as before (see vignette).

  • changed the complicated color_profile argument into three separate arguments - a color_type similar to color_profile$type argument before, a colors argument allowing user to choose a cohort of colors, and a color_seed argument allowing the user to sample different colors from the cohort. We now provide a default cohort of colors as well as default color_type in per-row (see vignette). The user now can do with not worrying about defining color_profile at all, and use the defaults instead and change the default cohort by color_seed. (see vignette).

  • added a return_heights option in logomaker() function that, when set to TRUE, returns the information of the heights of the stacks used for both standard and EDLogo (see vignette).

  • added a use_dash argument that, when set to TRUE, would automatically detect if the input is a character sequence of PFM matrix and perform adaptive scaling of heights (see vignette).

  • updated the vignette completely with major focus on the EDLogo representation and the use of the current logomaker() functionality

  • updated the README - with citation information and a demo example added.

  • Updated the gallery codes ( here to conform to the new system of functions.

  • Updated the HTML vignette ( to match with the pdf version of the vignette attached with the package.

  • updated README with examples from String logos (histones and mutation signatures).

  • moved from having data under inst/extdata to the data folder.

  • added a demo folder containing some test gallery examples.

Changes in version 1.2.1:

  • Added EDLogo plots highlighting both enrichment and depletion

  • Added new fill and border styles for the logos

  • Added a Dirichlet Adaptive Shrinkage (dash) for adaptively scaling position weights

  • Added tutorials in the vignette for multi panel Logos plots and combining Logolas plots with ggplot2 graphics.

  • Some input arguments are deprecated or passed into control parameters

  • Background matrix or vector option has been added for comparative logo plot visualization given a prior belief.

  • PSSM logo plot function added primarily for protein sequence motif visualization

  • Functions added to compute the heights of the enrichments and depletions of the symbols in logo plot.

  • Nomenclature added for calling a base at each position.

  • Deprecated depletion weight input for unscaled logos + added unscaled log and probKL and wKL approaches to the set of possible logos


Changes in version 1.6.00:


  • clinicalEnrichment - Performs mutational enrichment analysis for a given clinical feature.

  • signatureEnrichment - Performs sample stratification based on signature exposures and enrichment analysis.

  • plotEnrichmentResults - Plots results from clinicalEnrichment and signatureEnrichment analysis

  • lollipopPlot2 - Compare two lollipop plots


  • Forstplot now includes summary table within the plot.

  • Included capture_size argument in tcgaCompare.

  • annovarToMaf can take multiple annovar annotation files and converts them to a single MAF cohort.


Changes in version 0.99.19:

  • Beutify figures.

  • Remove some unnecessary dependencies.

Changes in version 0.99.18:

  • Add HeatmapView and BatchRemove.

  • Change view distribution functions which show samples separately.

  • Change function ReadBeta to be more friendly.

  • Label top ten essential genes in SquareView.

  • Change some default parameter values to be better.

Changes in version 0.99.10:

  • Change all plot function names ended with ‘View’.

  • Decrease exported functions

  • Decrease package denpendcies

  • Revise all documents

Changes in version 0.99.1:

  • Remove some new errors, such as error trigered by no GroupA genes.

  • Allow users to input their own essential genes to do the cell cycle normalization

  • Allow users to define the number of genes labeled in rank figure, default label top 10 and bottom 10 genes

  • Add annotation of other organisms

Changes in version 0.99.0:

  • FluteMLE and FluteRRA are two main functions in MAGeCKFlute package. FluteMLE run pipeline from gene beta scores caculated by MAGeCK MLE, while FluteRRA run pipeline based on MAGeCK RRA results.


Changes in version 1.5.4:


  • Added ‘struct’ convenience function for on-disk C-style structs (wrapper for ‘matter_list’)

Changes in version 1.5.3:


  • Added remainder of Summary group, including ‘range’, ‘min’, ‘max’, ‘prod’, ‘any’, and ‘all’ methods

  • Added options(matter.cast.warning=FALSE) for turning off C type coercion warnings

  • Exported low-level utilities ‘sizeof’, ‘make_datamode’, ‘convert_datamode’, and ‘widest_datamode’

  • Added ‘combiner’ generic function and method for setting/getting the ‘combiner’ for ‘sparse_mat’

  • Added ‘min’ and ‘max’ combiner functions for ‘sparse_mat’ matrices with tolerance > 0

  • Added ‘biglm’ method for ‘matter_df’ data frames


  • Fixed bug when coercing ‘matter_list’ to ‘matter_vec’

Changes in version 1.5.2 (2017-11-12):


  • All ‘matter’ subclasses now support endomorphic subsetting via ‘drop=NULL’ wherever appropriate

  • Setting the ‘dim’ slot via ‘dim<-‘ now switches the class between ‘matter_vec’ and ‘matter_arr’

  • Added ‘virtual_mat’ class for virtual matrices


  • Use ‘drop=NULL’ from now on instead of ‘drop=NA’ to do endomorphic subsetting of matter matrices

  • Added ‘matter_vt’ virtual class for matter objects which may exist both on-disk and in-memory

  • Added ‘matter_tbl’ virtual class for data tables


  • Fixed read/write bug when subsetting across atoms

Changes in version 1.5.1:


  • Added ‘sparse_mat’ class for sparse matrics (potentially on-disk) with subclasses ‘sparse_matc’ for CSC matrices and ‘sparse_matr’ for CSR matrices

  • Added ‘bsearch’ function for fast binary searches

  • Added ‘uuid’ function for generating UUIDs as both ‘raw’ and and ‘character’ vectors

  • Added a ‘checksum’ method for doing sha1 and md5 checksums of all files associated with a ‘matter’ object


Changes in version 0.99.0:

  • mCSEA release.


Changes in version 1.99.9 (2018-04-02):

  • This version is in prepration for the version 2.0

  • The MgDb-class definition was been redefined.

  • To reduce memory usage the and sequence data is now stored in the SQLite file along with the taxonomy data.

  • The mgFeatures-class now extends the DataFrame-class instead of the AnnotatedDataFrame-class so that mgFeatures can be used to define the rowData slot in a summarizedExperiment-class object.

  • The vignettes have been revised and new vignettes were added providing examples for working with the new class definitions.

  • Along with the new class definitions we have annotation packages for the three major 16S rRNA databases, SILVA, RDP, and Greengenes.

  • Greengenes version 13.8 85% similarity OTUs database is now included in the package.


Changes in version 1.21:

  • Numerous changes. Added greater flexibility to fitFeatureModel


Changes in version 0.99.0:


  • This is the first iteration of the MetaGxOvarian package. It is essentially an updated version of the curatedOvarianData package with 5 additional datasets


Changes in version 1.15.1:

  • Version bump to get inline with the Bioconductor number


Changes in version 1.19.14 (2018-04-12):


  • New option for count.type: when “transcript”, the DE analysis is performed at the transcript level. Only works for Ensembl annotation.


  • Fixed a leftover which prevented completing the analysis when count.type is “exon”.


Changes in version 1.3.20:

  • Standalone mode introduced, a version of epiviz with reduced capabilities is now included as part of epivizr. The epiviz web app is run locally using ‘httpuv’s http server

  • Add and remove seqinfo (e.g., chromosome info) to any epiviz session

Changes in version 1.3.11:

  • Add NEWS file

  • Update documentation on ‘slideshow’ function

Changes in version 1.3.10:

  • Changed default on ‘slideshow’ to show all ranges

Changes in version 1.3.9:

  • Added ‘heatmapChart’ convenience function

Changes in version 1.3.8:

  • Fixed bug in ‘startEpiviz’ not sending ‘seqName’ parameter correctly

Changes in version 1.3.7:

  • Fixed bug in ‘EpivizBpData’ that sent ‘metadata’ info in wrong format

Changes in version 1.3.6:

  • Changes slots using lists in ‘EpivizDeviceMgr’ to environments to avoid crashing RStudio due to inspection of manager objects

Changes in version 1.3.5:

  • Fails gracefully on daemonization request on Windows

  • Deprecates the ‘proxy’ argument to ‘startEpiviz’

Changes in version 1.3.4:

  • Upgrading to Epiviz v2 webapp


Changes in version 1.9.1:

  • no changes, check if package passes R CMD build and R CMD check without any error messages and vignette can be run without any errors [2018-04-16 Mon]

Changes in version 1.7.0:

  • implement calculation for parameter m = 0 in NDP [2017-11-14 Tue]


Changes in version 1.1.1:


  • Vignette describes methylation status calling in windows.

  • Vignette describes methylation status calling with a separate-context model.

  • Data import with data.table::fread for faster performance.


Changes in version 1.5.3:


  • resolve absolute paths for dbdir argument

  • initial check if output tabix file already exists and if yes rename output file

Changes in version 1.5.2:


  • updated links to vignette and presentations in README

  • fixed missspelling in show method of methylRawList object

  • fixed getSampleID method for methylDiff object

  • correct a not working code snippet in the vignette


Changes in version 1.1.0:

  • An updated release of this package for Bioconductor 3.7, released April 2018.

  • This release primarily implements minor changes, including the use of colors in the plots produced by the visualization methods.


Changes in version 1.25:

  • Added preliminary support for DelayedArray-backed minfi objects. This allows disk-backed minfi objects (e.g., using HDF5). This functionality is currently recommended only for developers and advanced users. A user-friendly interface is currently in development. All existing minfi functionality and serialized objects should continue to work as it did in versions prior to 1.25. Please report any problems to the GitHub issue tracker.

  • Fixing bug in functions readGEORawFile() and getGenomicRatioSetFromGEO(). These two functions did not work (reported an error). They should work now. Thanks to users who reported problems at GitHub issues.

  • Updated CITATION and citations in the vignette.


Changes in version 1.7.2:


  • getMirnasForMirbaseVersion: Retrieve all mature or precursor miRNA names from one or several miRBase version(s) and species


  • Updated vignette


  • o


Version: 1.5.2 Category: Update ground truth for validation <2018-04-17, Tues Text:

Version: 1.5.1 Category: Update netModule and spongeValidate function <2018-04-16, Mon Text:

Version: 1.5.0 Category: Update Reference Manual <2018-04-15, Sun Text:

Version: 1.3.3 Category: Update netModule function <2018-04-12, Thur Text:

Version: 1.3.2 Category: Update DESCRIPTION <2018-03-07, Wed Text:

Version: 1.3.1 Category: Update Reference Manual <2018-03-03, Sat Text:

Version: 1.3.0 Category: Update Reference Manual <2018-02-28, Wed Text:


Changes in version 1.59.2:

  • Fix warning stemming from base::seq_len in MLInterfaces:::MLIConverter.svm <2018-04-12 Thu>

  • Ammend xvalSpec man page <2018-04-12 Thu>

Changes in version 1.59.1:

  • Accommodate new points3d syntax in threejs::scatterplot3d for plspinHcube <2018-01-20 Sat>

  • remove references to rgl, it is not loading on MacOS and threejs seems to suffice


Changes in version 2.6.1:

  • knn-based density peak clustering is not general for all datasets. Rolled back to the previous densityPeak clustering algorithm and set it to be the default algorithm. A new Louvain clustering algorithm for dealing with large datasets (> 50 k cells) is added.

  • A few bug fixes for importCDS, exportCDS functions.


Changes in version 1.3.2:

  • Changed contact information


Changes in version 1.23.12:

  • Silence importMatrix for scan.

Changes in version 1.23.11:

  • Fix the bug in importMatrix for meme files.

Changes in version 1.23.10:

  • Fix the bug in importMatrix for meme files.

Changes in version 1.23.9:

  • Fix the warning in windows.

Changes in version 1.23.8:

  • Update the documentation plotMotifStackWithRadialPhylog.

Changes in version 1.23.7:

  • Update vignette.

Changes in version 1.23.6:

  • Add citation.

Changes in version 1.23.5:

  • Update authors email.

Changes in version 1.23.4:

  • create global environment to save tmp values.

Changes in version 1.23.3:

  • change the colorset name from colorBlindness to blindnessSafe

Changes in version 1.23.2:

  • fix some bugs in documentation.

Changes in version 1.23.1:

  • add a new color set for color blind safe.


Changes in version 1.12.0:

  • release as part of Bioconductor 3.7

Changes in version 1.11.2:

  • fix of code for using custom substitution matrices in ClustalW

Changes in version 1.11.1:

  • minor fix in ClustalW

Changes in version 1.11.0:

  • new branch for Bioconductor 3.7 devel


Changes in version 2.5.14:

  • Fix changed remote location of mzTab example files <2018-04-19 Thu>

  • Fix failing centroided unit test (see issue #338) <2018-04-20 Fri>

Changes in version 2.5.13:

  • Reduce unit testing time (see #334) <2018-04-13 Fri>

  • Fix bug in write.exprs when only one feature data is passed <2018-04-17 Tue>

Changes in version 2.5.12:

  • Ensure tic and bpi with initial = TRUE calculate the tic and bpi from the data (related to issue #332). <2018-04-10 Tue>

Changes in version 2.5.11:

  • Improve combineFeatures manual to document the effect for missing values for different types of aggregation methods <2018-04-07 Sat>

  • Update robust summary to hangle missing values (see #330). <2018-04-09 Mon>

Changes in version 2.5.10:

  • New robust summarisation method in combineFeatures contributed by Ludger Goeminne, Adriaan Sticker and Lieven Clement <2018-04-03 Tue>

  • Adapt utils.removePeaks to new IRanges implementation; thanks to H. Pagès for the implementation (see PR #320 for discussion) <2018-03-26>.

  • Centroiding information is retrieved from raw files (for mzML/mzXML files;. see issue #325 <2018-03-27>

  • Add parameter timeDomain to combineSpectra, combineSpectraMovingWindow and estimateMzScattering allowing to perform the grouping of m/z values from consecutive scans based on the square root of the m/z values <2018-03-29>.

  • Assure feature CV feature variable names are unique when combining feature repeatedly (see issue #303) <2018-04-04 Wed>

Changes in version 2.5.9:

  • New combineSpectra, combineSpectraMovingWindow, estimateMzScattering and estimateMzResulution functions <2018-03-05>.

  • New vignette describing profile mode data centroiding <2018-03-05>.

Changes in version 2.5.8:

  • New as(MSnExp, data.frame) method <2018-02-16>

  • Speed up readMgfData function - see issue #319 <2018-03-13 Tue>

Changes in version 2.5.7:

  • MSmap constructor for OnDiskMSnExp objects (see issue #305) <2018-01-31 Wed>

  • New filterMsLevel,MSnSet method <2018-02-06 Tue>

Changes in version 2.5.6:

  • Fixing processing message when combining two MSnSets (reported by kamal.fartiyal84 <2018-01-24 Wed>

Changes in version 2.5.5:

  • Added TMT11-plex <2018-01-17 Wed>

  • Add phenoData<- method for pSet (issue #299 <2018-01-22>.

  • Change readMSnSet2 example <2018-01-23 Tue>

Changes in version 2.5.4:

  • Add featureData slot to Chromatograms class and add mz, precursorMz and productMz methods for Chromatograms (issue #289) <2017-12-18 Mon>.

  • Add readSRMData function to read chromatographic data from SRM (MRM) experiments; issue #286 <2018-01-10 Wed>.

  • The MSnSetList class has a new featureData slot, accessible with fData to store metadata for the individial MSnSets of the list. MSnSetList also not has an sapply method. <2018-01-10 Wed>

  • combineFeatures now has a new fcol argument (see issue #195) <2018-01-11 Thu>

Changes in version 2.5.3:

  • Add filterPrecursorScan for MSnExp and OnDiskMSnExp; closes issue #282 and PR #287 <2017-12-16 Sat>.

  • MSnSet to/from SummarizedExperiment coercion (contributed by Arne Smits in PR #284) <2017-12-17 Sun>

  • Fix inverted M/Z axis in plot3D,MSmap (reported by Sylvain Dechaumet, see issue #292) <2017-12-19 Tue>

Changes in version 2.5.2:

  • Use automatic backend detection (based on file name and file content) that was introduced in mzR version 2.13.1 (issue #275).

  • Fix mzML file writing unit tests to work with recently introduced header column “filterString” (issue #278).

  • Reduce number of comparsions in in internal fastquant_max to get little speed improvents for isobaric quantification (see PR #280) <2017-11-27 Mon>.

  • MIAxE, MSnProcess and AnnotatedDataFrame coercion to list methods (in related to PR #280) <2017-12-11 Mon>

  • Add support to reduce the featureData for OnDiskMSnExp objects (issue #285) <2017-12-11 Mon>.

Changes in version 2.5.1:

  • Update dependencies (see issue #271)

  • Replace HCD by ETD in TMT10ETD’s name/description

Changes in version 2.5.0:

  • New version for Bioc 3.7 (devel) # MSnbase 2.4


Changes in version 1.5.1:

  • Updates for database creation (can use CAMERA objects now)

  • averageSpectra parameter ‘MSFileReader’ deprecated MSFileReader. Should use csvFile instead, MSFileReader option will still work but a warning will be given

Changes in version 1.4.1:

  • Updates for Galaxy for Spectral Matching

  • Spectral matching ra_thres_t bugfix

  • Separation of sqlite database creation. Now can be called on it’s own or with frag4feature (allows the Galaxy tool to be simplified)


Version: 3.11.6 Date: 2018-04-23 Text: BUG FIXES - SkylinetoMSstatsFormat : fix the inconsistency of column name from Skyline output

Version: 3.11.5 Date: 2018-02-22 Text: BUG FIXES - add the package, stringr, for DIAUmpiretoMSstatsFormat function

Version: 3.11.4 Date: 2018-02-19 Text: BUG FIXES - add set.seed for sample size calculation of classification

Version: 3.11.3 Date: 2018-02-15 Text: BUG FIXES - nonlinear_quantlim : fix the bug for the resampling of the blank sample, increase the default number of bootstrap samples - designSampleSize : fix the bug NEW FEATURES - new function : designSampleSizeClassification, designSampleSizeClassificationPlots - Calculate the optimal size of training data for classification problem by simulation. - new converter functions : DIAUmpiretoMSstatsFormat, OpenMStoMSstatsFormat

Version: 3.10.5 Date: 2018-01-10 Text: BUG FIXES - SpectronauttoMSstatsFormat : TRUE or FALSE are allowed for the values of the column, F.ExcludedFromQuantification. Check the value for this column.

Version: 3.10.4 Date: 2017-12-22 Text: BUG FIXES - MaxQtoMSstatsFormat : ‘fewmeasurements’ bug fixed

Version: 3.10.2 Date: 2071-11-27 Text: BUG FIXES - make error messages for QQ plot and residual plot, if the protein couldn’t be fitted by linear mixed effect model. - ProgenesistoMSstatsFormat : make more generalization for different format.


Changes in version 11-14-17:

  • -Package version pushed to 1.8.1 -Fixed package vignette issue with loading heat map image


Version: 3.6 Category: MutationalPatterns v1.3.2 (Release date: 2017-10-24 Text:

Version: 3.6 Category: Bugfixes Text: Removed deprecated functions from previous release.

Version: 3.6 Category: Bugfixes Text: Improved examples in documentation.

Version: 3.6 Category: MutationalPatterns v1.3.1 (Release date: 2017-10-24 Text:

Version: 3.6 Category: Bugfixes Text: Fix running of the code examples.

Version: 3.6 Category: MutationalPatterns v1.3.0 (Release date: 2017-10-22 Text:

Version: 3.6 Category: Bugfixes Text: To determine the transcriptional strand of mutations in genes, all mutations that overlap with multiple genes were excluded. When these genes are on different strands, it can indeed not be determined whether a mutation is on the transcribed or untransribed strand. However, if these overlapping genes are all on the same strand, the transcriptional strand can be determined, but these were unneccesarily removed from the analysis. This bug is now fixed, and as a result more mutations are now included in the analysis. This bugfix influences the results of: ‘mut_strand’ (previously ‘strand_from_vcf’) and ‘mut_matrix_stranded’

Version: 3.6 Category: Renamed functions Text: ‘strand_from_vcf’ to ‘mut_strand’

Version: 3.6 Category: Renamed functions Text: ‘mutation_types’ to ‘mut_type’

Version: 3.6 Category: Renamed functions Text: ‘mutation_context’ to ‘mut_context’

Version: 3.6 Category: New features & parameter changes Text: Replicative strand bias analyses - ‘mut_strand’ and ‘mut_matrix_stranded’ can now be executed in two modes: ‘transcription’ (default) or ‘replication’ - All downstream analyses can be performed for both modes with ‘strand_occurrences’, ‘strand_bias_test’ and ‘plot_strand_bias’

Version: 3.6 Category: New features & parameter changes Text: Condensed plotting option for ‘plot_96_profile’ and ‘plot_192_profile’ condensed = F (default), or condensed = T

Version: 3.6 Category: New functions Text: ‘plot_contribution_heatmap’: to visualize the relative contribution of mutational signatures in a heatmap. Samples can be hierarchically clustered.

Version: 3.6 Category: New functions Text: ‘cos_sim’: to calculate the cosine similarity between two vectors.

Version: 3.6 Category: New functions Text: ‘cos_sim_matrix’: to calculate all pairwise similarities between mutational profiles

Version: 3.6 Category: New functions Text: ‘cluster_signatures’: to hierarchically cluster signatures based on cosine similarity

Version: 3.6 Category: New functions Text: ‘plot_cosine_heatmap’: to visualize pairwise cosine similarities between mutational profiles in a heatmap Sample can be hierarchically clustered.

Version: 3.6 Category: MutationalPatterns v1.1.3 (Release date: 2017-04-20 Text:

Version: 3.6 Category: Fourth preparation release for Bioconductor 3.5 Text:

Version: 3.6 Category: Bugfixes Text: Add missing package to ‘Suggest’ field.

Version: 3.6 Category: MutationalPatterns v1.1.3 (Release date: 2017-04-20 Text:

Version: 3.6 Category: Third preparation release for Bioconductor 3.5 Text:

Version: 3.6 Category: Bugfixes Text: Fix running of a unit test.

Version: 3.6 Category: Bugfixes Text: Fix another build problem for Windows.

Version: 3.6 Category: MutationalPatterns v1.1.2 (Release date: 2017-04-18 Text:

Version: 3.6 Category: Third preparation release for Bioconductor 3.5 Text:

Version: 3.6 Category: Bugfixes Text: Properly read external data for tests.

Version: 3.6 Category: Bugfixes Text: Fix build problems on Windows.

Version: 3.6 Category: MutationalPatterns v1.1.1 (Release date: 2017-04-12 Text:

Version: 3.6 Category: Second preparation release for Bioconductor 3.5 Text:

Version: 3.6 Category: MutationalPatterns v1.1.0 (Release date: 2017-04-06 Text:

Version: 3.6 Category: Preparations for Bioconductor release 3.5 Text:

Version: 3.6 Category: Interface changes Text: ‘read_vcfs_as_granges’: The ‘genome’ parameter must now be the name of a BSgenome library, to prevent problems with seqlevels style. The function now accepts an optional ‘group’ parameter to use a subset of chromosomes. It also accepts the new optional ‘check_alleles’ parameter to significantly speed up the reading of VCF files.

Version: 3.6 Category: Interface changes Text: ‘plot_contribution’: This function now accepts an optional parameter ‘palette’ to specify custom colors.

Version: 3.6 Category: Performance updates Text: Implement parallel execution in ‘read_vcfs_as_granges’, ‘mut_matrix’ and ‘mut_matrix_stranded’.

Version: 3.6 Category: Bugfixes Text: Fix ‘mut_type_occurences’ to handle missing types.

Version: 3.6 Category: Bugfixes Text: Fix ‘mut_matrix’ and ‘mut_matrix_stranded’ to emit warnings when processing empty GRanges.

Version: 3.6 Category: Bugfixes Text: Fix inconsistencies in the README and the vignette.

Version: 3.6 Category: Other changes Text: Various vignette updates.

Version: 3.6 Category: Other changes Text: Added unit tests for ‘read_vcfs_as_granges’, ‘mut_matrix’, and ‘mut_matrix_stranded’.

Version: 3.6 Category: MutationalPatterns v1.0.0 (Release date: 2016-10-19 Text:

Version: 3.6 Category: Bioconductor release 3.4 Text:

Version: 3.6 Category: MutationalPatterns v0.99.6 (Release date: 2016-10-14 Text:

Version: 3.6 Category: Changes Text: Renamed functions: ‘mut_type_occurences’ to ‘mut_type_occurrences’, ‘strand_occurences’ to ‘strand_occurrences’.

Version: 3.6 Category: MutationalPatterns v0.99.5 (Release date: 2016-10-06 Text:

Version: 3.6 Category: Changes Text: Added deprecation and defunct messages to functions that have changed since the v0.99.0.

Version: 3.6 Category: Changes Text: Various small vignette and reference manual updates.

Version: 3.6 Category: MutationalPatterns v0.99.4 (Release date: 2016-10-05 Text:

Version: 3.6 Category: Changes Text: Internal package loading changes.

Version: 3.6 Category: Changes Text: Removed files that do not belong to the package.

Version: 3.6 Category: MutationalPatterns v0.99.3 (Release date: 2016-09-28 Text:

Version: 3.6 Category: Changes Text: Renamed functions: ‘get_mut_context’ to ‘mutation_context’, ‘get_type_context’ to ‘type_context’, ‘get_muts’ to ‘mutations_from_vcf’, ‘get_strand’ to ‘strand_from_vcf’.

Version: 3.6 Category: Changes Text: Added an explanation for the difference between SomaticSignatures and MutationalPatterns in the vignette.

Version: 3.6 Category: MutationalPatterns v0.99.2 (Release date: 2016-09-23 Text:

Version: 3.6 Category: Changes Text: Renamed functions: ‘vcf_to_granges’ to ‘read_vcfs_as_granges’, ‘get_types’ to ‘mutation_types’.

Version: 3.6 Category: MutationalPatterns v0.99.1 (Release date: 2016-09-13 Text:

Version: 3.6 Category: Changes Text: Renamed functions: ‘read_vcf’ to ‘vcf_to_granges’.

Version: 3.6 Category: Changes Text: Removed functions: ‘bed_to_granges’, ‘estimate_rank’, ‘rename_chrom’.

Version: 3.6 Category: Changes Text: Parameter changes: ‘plot_rainfall’, ‘vcf_to_granges’

Version: 3.6 Category: MutationalPatterns v0.99.0 (Release date: 2016-09-12 Text:

Version: 3.6 Category: Changes Text: Package created


Changes in version 2.13.8:

  • Document missing chrom argument for chromatogram(s)

Changes in version 2.13.7:

  • Add a missing header needed on gcc 6.2.0

Changes in version 2.13.6:

  • Add MS CV Term IDs for mzR, MSnbase and CAMERA (issue #151)

  • Validate exported mzML files using xsd

Changes in version 2.13.5:

  • Fix

  • Fix endian.hpp for new c++ versions (see PR #149)

Changes in version 2.13.4:

  • Fix error (see issue #145)

Changes in version 2.13.3:

  • Link against Rhdf5lib, allows to read mz5 also on Windows

  • Use Rhdf5lib 1.1.4 with c++ headers in /include

  • fix BiocStyle related issue in Vignette on Windows

Changes in version 2.13.2:

  • Add chromatogramHeader method to read header information for chromatograms from an mzML file.

Changes in version 2.13.1:

  • Read filter string from mzML files and add it to the data.frame returned by the header function (see MSnbase issue #278).

  • openMsFile automatically determine the backend to use based on file extension and content.


Changes in version 1.1.7:

  • FIX: error in RCX => RCXgraph => RCX conversion

  • FIX: NDEx server update for return columns in network list, summary and metadata; metadata also not nested anymore

  • FIX: tests crashed because of missing network; updated used UUID to new version of the public one from ndextutorials

  • exclude ..Rcheck from git; added “ndexr” to user agent header

  • FIX: build error caused by ‘metadata:properties’ now being optional

  • UPDATE: minor bugfixes due to ndex server update. Added api for ndex server version 2.2

Changes in version 1.1.2:

  • Breaking changes of the class and function names! NGraph was renamed to RCXgraph to avoid naming Disambiguities! Deprecated Functions:

  • rcx_toRCXgraph

  • rcxgraph_fromRCX

  • rcxgraph_toRCX

  • rcx_fromRCXgraph Therefore the new funtions are called:

  • rcx_toRCXgraph

  • rcxgraph_fromRCX

  • rcxgraph_toRCX

  • rcx_fromRCXgraph


Changes in version 2.22.1 (2018-02-01):

  • Fixed some bugs.


Version: 0.99.9 Date: 2017-10-14 Category: Initial release to Bioconductor Text:


Changes in version 0.99.4:

  • changed vignette to html instead of pdf.

  • edited vignette.

Changes in version 0.99.3:

  • bug fix. extrainformation.rmd changed to extrainformation.Rmd.

Changes in version 0.99.0:

  • release version.


Changes in version 2.10.0:

  • probDetect mechanism changed. This could be a BREAKING CHANGE. The expression divides by the baseline. For fixed initSize, this is simply a matter of changing the cPDetect.

  • fixation allows exact genotypes, includes tolerance, and checks for a successive number of specified periods

  • LOD: using only the strict Szendro et al. meaning.

  • POM: computed in C++.

  • Using fitness landscape directly when given as input (no conversion to epistasis) and several improvements in speed when using fitness landscapes as input.

Changes in version 2.9.10 (2018-04-19):

  • test.Z-fixation: some tests only on Linux because rng is done in C++.

Changes in version 2.9.9 (2018-04-10):

  • probDetect mechanism changed. This could be a BREAKING CHANGE. The expression divides by the baseline. For fixed initSize, this is simply a matter of changing the cPDetect.

Changes in version 2.9.8 (2018-03-26):

  • fixation allows exact genotypes, includes tolerance, and checks for a successive number of specified periods

Changes in version 2.9.7 (2018-02-20):

  • fixed crash in some conditions when run with stringsAsFactors = FALSE as global option

Changes in version 2.9.6 (2017-12-27):

  • Updated citation.

  • An example (in miscell-files) about using and stopping with modules.

  • Prototype for sampling the single larges pop at last period (function largest_last_pop, commented out for now).

Changes in version 2.9.5:

  • samplePop: new option “single-nowt”

Changes in version 2.9.4 (2017-11-30):

  • Deal with the very rare NULL simulations in summary.

Changes in version 2.9.3 (2017-11-27):

  • Make clang happy (do not use flandscape as DataFrame)

Changes in version 2.9.2 (2017-11-24):

  • LOD: using only the strict Szendro et al. meaning.

  • POM: computed in C++.

Changes in version 2.9.1 (2017-11-10):

  • Using fitness landscape directly when given as input (no conversion to epistasis)


Changes in version 1.0.0:

  • first release of ORFik - find Open Reading Frames, automatic RiboSeq footprint shifts, reassignment of Transcription Start Sites with the use of CageSeq, plethora of gene identity functions from scientific publications


Changes in version 1.7.0:

  • Fix a bug in creation of GO graph where invalid edges were included


Changes in version 1.8.1:

  • Update data uploading

  • Modify visualization

  • Add biomarker tab


Changes in version 1.18.2:

  • korg now include 5245 KEGG species. To speed up pathview package loading, an updated version of korg is now checked out from Pathview Web server only when it is acutally used and needed.


Changes in version 2.6.0:


  • Automatically computing size factors where required

  • Added progress indication when compiling the report


  • Fixed after changes in threejs package

  • Edited dropdown menu to remove unused green badge

  • Menus start expanded on the side, again

  • theme_bw applied when needed, corrected previous behavior


  • Updated citation infos

  • Slight difference in handling validate/need errors


Changes in version 1.9.1:

  • As the “getTable()” of rtracklayer would produce a Bad Request error. We temporarily disabled the code checking of the “PrepareAnnotationRefseq2” function until the bug had been fixed. Please use the “PrepareAnnotationEnsembl2” to prepare the annotation file instead of “PrepareAnnotationRefseq2”.


Changes in version 0.99.34:

  • Detecting conditions and replicates in GEO data

Changes in version 0.99.28:

  • Submit to Enrichr tool

  • Changing shapes in PCA plot

  • Better support for OS X and Windows

Changes in version 0.99.24:

  • Shiny GAM tool added

  • PCA plot: pretty labels, auto-redraw

  • Bug fixes

Changes in version 0.99.23:

  • Added options “Maximum Mean Probe” and “Maximum Median Probe” to Collapse Tool

  • Fixed a bug emerging when one applies R-based function after collapsing by columns

Changes in version 0.99.22:

  • Fixed AdjustTool

  • Removed obsolete output produced by servePhantasus

  • Updated tutorial

Changes in version 0.99.21:

  • Merged changes from morpheus.js repository

  • Added function reparseCachedESs for updating downloaded GEO-datasets, which are saved in cache

Changes in version 0.99.20:

  • A bit better code coverage with tests

Changes in version 0.99.19:

  • Safer procedure for phenoData parsing

  • Even sample-empty datasets deserve to have displayed meta

Changes in version 0.99.18:

  • New phenoData parsing strategy for GEO Series

Changes in version 0.99.17:

  • Fixed issue with null featureData for GSE37270

Changes in version 0.99.16:

  • Fixed issue with incorrect perfomance of LimmaTool when columns are passed as args

Changes in version 0.99.15:

  • Updated tutorial

Changes in version 0.99.14:

  • Correct error messages when dataset is not present in GEO

Changes in version 0.99.13:

  • Added possibility to load datasets from preloaded rda-files in specialized directory on server

  • servePhantasus now opens browser with web-application automatically on start-up

  • Added tutorial on main site

  • Updated biocViews

  • Updated tutorial and mans according to changes

  • Added experimental support for loading RNA-seq dataset from GEO

Changes in version 0.99.12:

  • Added possibility to load GEO-dataset by specifying its id in link parameters


Version: 1.20.0 Category: none yet Text:

Version: 1.18.1 Category: BUG FIXES Text: Fix parsing of gmt files when gene-set name contains spaces


Changes in version 1.5.22 (2018-04-28):

Bug Fixes

  • stats::cor is used in compute.pigengene and draw.cor functions. See the NAMESPACE for the important reason.

Changes in version 1.5.9 (2018-03-12):


  • cor is imported from WGCNA, but not from stats, because WGCNA does not call the cor function properly.

Changes in existing functions

  • RsquaredCut is added to the arguments of the one.step.pigengene function.

Changes in version 1.5.6 (2018-01-19):

Changes in existing functions

  • In the get.fitted.leaf function, the function is used, which used to be exported in the previous versions of C50, but not in version 0.1.1.

Changes in version 1.5.2 (2017-11-10):

New functions

  • The check.nas function is now exported.


Version: 1.99.3 Text: NB function now exported

Version: 1.99.3 Text: note that version 1.99.3 on GitHub was version 1.1.0 on Bioconductor.

Version: 1.99.2 Text: bug fix in fragment generation (last 2 bases of transcript were never sequenced)

Version: 1.99.1 Text:


Changes in version 0.99.0:

  • The review version.


Version: 0.1.1 Category: Getting compliant with BioConductor policies Text:

Version: 0.1.1 Category: INITIAL RELEASE Text:


Changes in version 1.19.4:

  • Fix regression bug in knntl function <2018-04-12 Thu>

Changes in version 1.19.3:

  • Use dplyr::left_join without attaching dplyr to avoid collision between Biobase::exprs and dplyr::exprs <2018-04-04 Wed>.

  • Typo in warning to install rgl <2018-03-27 Tue>

Changes in version 1.19.2:

  • Fix bug in QSep that prevented to set non-default fcol <2018-01-29 Mon>

Changes in version 1.19.1:

  • Fix bug in private dimred and set appropriate number of colnames <2017-11-07 Tue>

  • New nipals method in dimensionality reduction for plot2D (closes issue #103) <2018-01-16 Tue>

Changes in version 1.19.0:

  • Bioconductor devel 3.7


Changes in version 1.11.13:


  • Normalization: “Sum by columns” has been modified to provide log-abundances compatibles with the other treatments. It can be done “for each condition independantly” or “globaly”.


  • Descriptive statistics: The expression datasets are colored w.r.t the nature of missing value (POV or MEC) even when the value has been imputed

  • Filtering: Manage designs with more than 2 conditions and with conditions containing different number of samples

  • Filtering: UI more user friendly for the string-based filtering (Tab 2)

  • Normalization: A few modifications in the UI and

  • Imputation (protein level): Distinction between missing values on an entire condition (Missing on the Entire Condition) and the other ones (Partially Observed Value)

  • Imputation (protein level): for the POV, it is possible to use SLSA which take into account the experimentaldesign experimental

  • Imputation (protein level): imputations are all processed condition by condition

  • Differential analysis: All tests can process datasets with conditions of different number of samples

  • Differential analysis: Limma takes into account all the hierarchical experimental designs

  • GO analysis: Add the GeneID nomenclature.

Changes in version 1.11.4:


  • A bug in the string-based filtering tool was fixed. The case where an entity could be both contaminants and reverse was not takien into account.This lead to wrong number in the plot.

  • Correction of the beahviour of the table in the experimental design (convert Data tool). When the user copy-paste some lines it may add unneeded rows. These rows can be deleted with an option in the contextual menu.


Changes in version 1.10.0:

  • New normal database format

  • Runtime performance improvements (skip unlikely local optima, support for BiocParallel in runAbsoluteCN, pre-calculation of mapping bias)

  • Support for replication timing scores in coverage normalization

  • More accurate confidence intervals in callMutationBurden

  • More accurate copy numbers for high-level amplifications

  • Very low or high coverage samples are now by default dropped in normal database creation (less than 25% or more than 4 times the median sample coverage)

  • Improved support for third-party upstream tools like GATK4 (experimental)

  • More checks for wrong or sub-optimal input and providing suggestions for fixing those issues

  • Gibbs sampling of log tumor/normal coverage error rate

  • Better imputation of mapping bias (instead of smoothing over neighboring variants in the sample, smooth over neighboring SNPs in the pool of normals - only available when pre-calculated)

  • Experimental support for indels

  • Code cleanups (switch to testthat, removed several obsolete and minor features) API CHANGES

  • renamed gc.gene.file to interval.file since it now provides more than GC-content and gene symbols

  • plotAbs ids changed to id (this function now only plots a single purity/ploidy solution)

  • changed default of runAbsoluteCN max.logr.sdev to 0.6 (from 0.75)

  • createTargetWeights does not require tumor coverages anymore

  • calculateGCContentByInterval was renamed to preprocessIntervals

  • renamed plot.gc.bias to plot.bias in correctCoverageBias since it now also includes replication timing

  • added calculateMappingBiasVcf to pre-compute mapping bias from a panel of normal VCF, thus avoiding time loading and parsing of huge VCFs

  • max.homozygous.loss now defines the maximum fraction of a chromosome lost, not the whole genome, to avoid wrong maximum likelihood solutions with completely deleted chromosome arms


Changes in version 1.17.1:

  • Remove deprecated html_document2 <2018-01-16 Tue>


Changes in version 2.14:


  • Added argument marginalization argument to qpPathWeight().


  • Bugfix in the ‘rUGgmm()’ function when called with an undirected graph defined by numeric (integer) vertices, to respect the numeric ordering of those vertex lables, i.e., avoid simulating a graph with ordered vertices “1”, “10”, “11”, etc., and get instead “1”, “2”, “3”, etc.


Changes in version 1.26.0:

  • Removed RCytoscape code and dependencies since RCytoscape is deprecated.


Changes in version 1.3.0:


  • Improved error reporting from parallel jobs

  • Improved logging behavior

  • Added multiple input checks in the pipeline functions

  • Improved MLK behavior in Microsoft R

  • Added BED and BedGraph export

  • Added Manhattan plot function

  • Added ROC curve with AUC calculation

  • Made fragment size estimation functions public

  • Made PCA plotting functions public

  • Added rwDataClass for convenient data access.

  • Added getLocations, getMWAS, getData functions

  • Improved QQ-plot function (more parameters)

  • Speed up pvalue2qvalue function for sorted vectors

  • Added multithreading in ramwas0createArtificialData()

  • Improved testPhenotype() to have consistent input (variables by columns)

  • BAM scanning [ramwas1scanBams] rescans BAMs newer than the rbam files


  • Use importMethodsFrom(filematrix, as.matrix) in NAMESPACE


Changes in version 1.9.1:

Minor changes

  • Vignette formating in order to meet the guidelines of the “Bioconductor LaTeX Style 2.0”.


Changes in version 0.99.7:

  • Main update: Re-formatted ranking databases. They are now loaded from .feather files (and therefore, they are transposed: motifs are stored as rows, and genes/regions as columns, which allows to load only specific genes/regions)

Changes in version 0.99.6:

  • Main update: Re-formatted annotation database. For easier subsetting.

Changes in version 0.99.1:

  • Main update: New class for the Rankings (rankingRcisTarget)

Changes in version 0.7:

  • Converted the ranking databases to an S4 class.

Changes in version 0.6:

  • Added function addLogo()

  • AUC is now returned as a class


Version: 2.0 Category: For Developers Text: Reorganized functions into files corresponding to CyREST API, e.g., Collections, CytoscapeSystem, Layouts, Networks, etc. Normalized all documentation using roxygen2 Streamlined interfaces to CyREST and Commands API (see above), greatly facilitating the implementation of any new functions matching CyREST or Command API additions Reverted all single-instance methods to simple functions, replacing class-based signatures with simple default values Established handy functions for validating network and view SUIDs getNetworkName getNetworkSuid getNetworkViewSuid

Version: 2.0 Category: Deprecated Text: Outdated function names

Version: 2.0 Category: Defunct Text: CytoscapeConnection and CytoscapeWindow classes, functions and parameters


Changes in version 1.23.2:

  • re-implement viewPathway <2018-03-15, Thu>

  • mv site to

Changes in version 1.23.1:

  • import enrichplot


Changes in version 1.5.11:


  • Change some examples to dontrun and improve the code that cleans up after the tests. This should reduce the size of files left in tmp although they didn’t seem too big to begin with.

Changes in version 1.5.9:


  • The functions add_metadata() and add_predictions() now return the sample metadata or predictions when the ‘rse’ argument is missing.

Changes in version 1.5.6:


  • Added the function add_metadata() which can be used to append curated metadata to a recount rse object. Currently, add_metadata() only supports the recount_brain_v1 data available at and to be further described in Razmara et al, in prep, 2018.

Changes in version 1.5.5:


  • Fix doc link in geo_characteristics() which affected the Windows build machines.

Changes in version 1.5.4:


  • Fix a unit test for download_study(), add another test for the versions, and fix a NOTE in R CMD check.

Changes in version 1.5.3:


  • download_study() can now download the transcript counts (rse_tx.RData) files. The transcript estimation is described in Fu et al, 2018.


  • download_study() now has a version parameter (defaults to 2). This argument controls which version of the files to download based on the change on how exons were defined. Version 1 are reduced exons while version 2 are disjoint exons as described in further detail in the documentation tab of the recount website

  • recount_url and the example rse_gene_SRP009615 have been updated to match the changes in version 2.


Changes in version 1.7.2 (2018-04-25):


  • New faster annotation building system which keeps also versions. May break older annotation stores. A rebuild is advised.

  • More supported genomes


  • Fixed a bug resulting in profile bleeding when using a mask of ranges from a BAM file.


Changes in version 1.28.0:

  • Regular maintenance, stable release.


Changes in version 1.11.1:

  • save regions in gzip file then submit to GREAT

  • will not change the content of the input regions


Changes in version 1.11.2:


  • updating dependencies caused a crash. Investigating. Biomart seems to no longer support “hsapiens_gene_ensembl” (sometimes/bug) Intermittent bug fixed in a later biomaRt edition.

  • R 3.5.0 support calls for a tweak in GOCatEngine.R


Changes in version 2.24.0:


  • Removed bundled HDF5 library - rhdf5 now depends on Rhdf5lib. This updates the version of HDF5 to 1.8.19.

  • Functions H5Ldelete() and h5delete() added to provide mechanisms for removing items from HDF files.

  • Added argument native to many functions, which allows data to be treated as row-major rather than column-major, improving portability with other programming languages.

  • Added function H5Sunlimited() allowing creation of extensible datasets - thanks to Brad Friedman


  • Datasets can now be subset using &#91; and a range of values e.g. did[,1:5].

  • Writing a data.frame that contains factors and setting DataFrameAsCompound=FALSE now works.

  • Many functions that would leave open file handles after exiting under error conditions have been fixed.

  • Performance improvements in h5read().


Changes in version 1.12.0:


  • The HTSlib C library was updated from version 1.1 to version 1.7.


Changes in version 1.7.2:

  • Corrected Biocstyle bug in author field of the vignette


Changes in version 1.11.9:

  • Bugfixes and improvements in gender prediction, GEO import, differential variability, installation and others

Changes in version 1.11.8:

  • Fixes for bioconductor warnings (combine, etc.)

  • docoupled missing value imputation from differential methylation

Changes in version 1.11.7:

  • enhanced cross-platform combination methods

  • improved installation routines

  • enhanced plots in exploratory analysis module

  • better LOLA annotation

  • improved performance of missing value imputation

  • documentation updates

  • several minor bugfixes

Changes in version 1.11.6:

  • Improved combining methods for RnBSet objects of different data types

  • Interpretation of sample mean methylation levels and other statistics

  • Improved plots in exploratory analysis module

  • Improved missing value imputation

  • Several minor bugfixes

Changes in version 1.11.5:

  • bugfixes (loading, imputation)

Changes in version 1.11.4:

  • Introducing RnBeadsDJ, a shiny-based interface for running RnBeads analyses and modules (run with

  • Added implementation of the LUMP algorithm for immune cell content estimation

  • The default normalization method was changed to “wm.dasen”

  • Background normalization is now disabled per default.

  • Option backwards compatibility

  • bugfixes (LOLA dependencies, 1-sample differential variability, QC visualization, …)

Changes in version 1.11.2:

  • Fixed a bug concerning failed trackhub exports on Windows


Changes in version 1.15.2:

  • Updated the vignette with a new url for gtf files

  • ranges() for Hits -> overlapsRanges()


Changes in version 2.7.2:

  • Nothing yet

Changes in version 2.7.1:

  • Fix failing partOf unit test <2017-11-27 Mon>

Changes in version 2.7.0:

  • Bioconductor devel 3.7


Changes in version 1.35.2 (2017-11-12):

  • phyloseq moved from dependency to import

  • vignette format updated

  • explicitly imported all functions


Changes in version 1.31:


  • (v.1.31.3) pileup() examples require min_base_quality = 10. See


Changes in version 0.99.0:

  • First release, only headers files have been included.


Version: 0.99.0 Category: Seattle time Text:

Version: 0.99.0 Category: Marc will contact you off-tracker for the follow-up Text:

Version: 0.99.0 Category: MS: If the version is set to 0.5, the package still goes to the release branch, or stays in devel Text:

Version: 0.99.0 Category: If it goes to release, I’m cool with that, it is still under construction, but functional Text:


Version: 1.30.0 Category: NEW FEATURES Text:

Version: 1.30.0 Category: o New parameters in featureCounts() to give more control on the size of overlap between read and feature - ‘nonOverlap’ and ‘nonOverlapFeature Text:

Version: 1.30.0 Category: o New parameter in featureCounts() to specify the path where files containing counting results for each read are saved - ‘reportReadsPath Text:

Version: 1.30.0 Category: o New parameter in align() and subjunc() to allow reads in the mapping output to have the same order as in the FASTQ file - ‘keepReadOrder Text:

Version: 1.30.0 Category: o Reduce running time in outputting BAM files in align() and subjunc() via saving data to disk with multi threads Text:

Version: 1.30.0 Category: o Annotation file (eg. GTF, SAF or VCF annotation) in featureCounts(), align(), subjunc() and exactSNP() can be provided as a gzipped file Text:

Version: 1.30.0 Category: o Tilda (‘~’) is allowed to be included in file names provided to functions. Text:

Version: 1.30.0 Category: o Improve running time of featureCounts for the processing of BAM files generated by some other aligners and the Picard tool Text:


Changes in version 2.4.0:

  • Improved RTN workflows.


Changes in version 1.4.0:

  • Improved workflow integration with derivative packages (RTN / RTNsurvival).


Changes in version 1.0.0:


  • Added derivative functions for both listPathways and getPathwaysByXref to allow specifying the return of simple lists of WPIDs, URLs or names.

  • Added support for PNG from getColoredPathway

  • Added functions for all remaining web service API methods

  • Added a download function for archived pathway sets in various formats

  • Added Overview and BridgeDbR vignettes


  • Updated all functions to use REST calls instead of Curl

  • Simplified function development by abstracting as dedicated wikipathwaysGET function

  • Added tests for all new functions

  • Added enumerated parameters in a number of places for better input validation


  • First official release. No bugs… yet!


Changes in version 0.18.0:


  • The package gets a new vignette: S4VectorsOverview.Rnw The material in this new vignette comes from the IRangesOverview.Rnw vignette located in the IRanges package. All the S4Vectors-specific material was moved from the IRangesOverview.Rnw vignette to the new S4VectorsOverview.Rnw vignette.

  • All Vector derivatives now support ‘x[i, j]’ by default. This allows the user to conveniently subset the metadata columns thru ‘j’. Note that GenomicRanges objects have been supporting this feature for years but now all Vector derivatives support it. Developers of Vector derivatives with a true 2-D semantic (e.g. SummarizedExperiment) need to overwrite this.

  • rank() now suports ‘by’ on Vector derivatives.

  • Add concatenateObjects() generic and methods for LLint, vector, Vector, Hits, and Rle objects. This is a low-level generic intended to facilitate implementation of c() on vector-like objects. The “concatenateObjects” method for Vector objects concatenates the objects by concatenating all their parallel slots. The method behaves like an endomorphism with respect to its first argument ‘x’. Note that this method will work out-of-the-box and do the right thing on most Vector subclasses as long as parallelSlotNames() reports the names of all the parallel slots on objects of the subclass (some Vector subclasses might require a “parallelSlotNames” method for this to happen). For those Vector subclasses on which concatenateObjects() does not work out-of-the-box or does not do the right thing, it is strongly advised to override the method for Vector objects rather than trying to override the (new) “c” method for Vector objects with a specialized method. The specialized “concatenateObjects” method will typically delegate to the method below via the use of callNextMethod(). See “concatenateObjects” methods for Hits and Rle objects for some examples. No Vector subclass should need to override the “c” method for Vector objects.

  • Major refactoring of [[<- for List objects. It’s now based on a new “setListElement” method for List objects that relies on [<- for replacement, c() for appending, and [ for removal, which are the 3 operations that setListElement() can perform (depending on how it’s called). As a consequence [[<- now works out-of-the box on any List derivative for which [<-, c(), and [ work.


  • endoapply() and mendoapply() are now regular functions instead of generic functions.

  • A couple of minor improvements to how default “showAsCell” method handles list-like and non-list like objects.

  • Replace strsplitAsListOfIntegerVectors() with toListOfIntegerVectors(). (The former is still available but deprecated in favor of the latter.) The input of toListOfIntegerVectors() now can be a list of raw vectors (in addition to be a character vector), in which case it’s treated like if it was ‘sapply(x, rawToChar)’.

  • A couple of optimizations to “[<-“ method for DataFrame objects (see commit e63f4cfd637e3471e4b04015c2938348df17e14a).


  • phead() and ptail() are deprecated in favor of IRanges::heads() and IRanges::tails().

  • strsplitAsListOfIntegerVectors() is deprecated in favor of toListOfIntegerVectors().


  • The mcols() setter no more tries to downgrade to DataFrame a supplied right value that extends DataFrame (e.g. DelayedDataFrame).

  • ‘DataFrame(I(x)) and as(I(x), “DataFrame”)’ now drops the I() wrapping before storing ‘x’ in the returned object. This wrapping was ugly, not needed, and breaking S4 objects.

  • Fix a couple of long-standing bugs in DataFrame subassignment: - Bug in the “[<-“ method for DataFrame objects where replacing the 1st variable with a rectangular object (e.g. x1 <- DataFrame(aa=I(matrix(1:6, ncol=2)))) was returning a DataFrame with the “nrows” slot set incorrectly. - A couple of bugs in the “replaceROWS” method for DataFrame objects when used in “rbind mode” i.e. when max(i) > nrow(x).

  • Fix bug in “cbind” method for DataFrame where it was appending X to the column names in some situations (see

  • Fix order() on SortedByQueryHits objects (see

  • Fix bug in internal new_Hits() constructor where it was not returning an object of the class specified via ‘Class’ in some situations.

  • “lapply” for SimpleList objects now calls internally to find the function to apply.


Version: 22.11.2017 Text:


Changes in version 1.7.18:

  • Refactored calculateQCMetrics() to ignore potential non-linearity, rank genes by highest expression, rename automatically generated union sets, allow for output of a compact format.

  • Refactored all plotting functions to allow access to nested fields in the colData() or rowData(), by supplying a character vector.

  • Refactored plotTSNE(), plotPCA(), etc. to dispatch to the calculation functions (e.g., runTSNE(), runPCA()), with argument checks.

  • Refactored plotColData() and plotRowData() to use the same argument types as other functions rather than aes= input.

  • Removed all plotting functions that do not operate on SingleCellExperiment objects.

  • Deprecated read10xResults(), downsampleCounts() in favour of methods from the DropletUtils package.

  • Deprecated scater_gui() in favour of methods from the iSEE package.

  • Deprecated normalizeExprs() as this function made very little sense.

  • Added plotHeatmap() function, for easy plotting of heatmaps.

  • Added librarySizeFactors() function, to compute size factors from library sizes.

  • Added by_exprs_values= argument to many plotting functions, to distinguish direct plotting of expression values from their use in aesthetics.

  • Renamed arguments in plotHighestExprs(), plotExprsVsTxLength(), plotExprsFreqVsMean() for greater clarity.

  • Added centreSizeFactors() function for centralized size factor centering.

  • Added size_factor_grouping= argument to normalizeSCE(), calcAverage() and calculateCPM().

  • Added subset_row= argument to calculateCPM().

  • Consolidated size_factors= argument into use_size_factors= for calcAverage(), calculateCPM().

  • Modified normalizeSCE() so that centre_size_factors=FALSE does not use centred size factors at all during normalization.


Changes in version 1.3.4 (2018-03-26):

  • The test for differences in proportion of zeroes now uses the Wald test p-value instead of the likelihood ratio. This will give very similar results, but the Wald test is slightly more conservative.

Changes in version 1.3.3 (2018-03-23):

  • An option has been added to skip the categorization step if only intereseted significance of difference. This will speed up computation.

  • The testing zeroes step and the KS test have been parallelized to speed up computation.


Changes in version 0.99.38:


  • scmeth is a package to analyze methylation data and it generates a comprehensive quality control report

  • Most functions take bsseq object as the input


Changes in version 1.0.9:

  • fix the bug that might misalign the exon mapping reads

  • support gff files from gencode or refseq

Changes in version 1.0.8:

  • update the gene id annotation code

Changes in version 1.0.6 (2017-12-18):

  • Now the id conversion can also be done by using the bioconductor annotation package, when biomart fails to connect.

Changes in version 1.0.5 (2017-12-14):

  • Fixed bugs in slim report and trimbarcode error message

  • Fix incomplete error message

  • Documentation updates, new functions and bug fixes

Changes in version 1.0.4 (2017-12-04):

  • In detect_outlier, give more informative error message when some cells or QC metrics have zero values.

Changes in version 1.0.3 (2017-12-03):

  • fix a bug in validObject. the default value for gene id and organism is set to NA

Changes in version 1.0.2 (2017-12-01):

  • fix errors in unittest

Changes in version 1.0.1 (2017-11-28):

  • Bug Fix: Fixed handling of colData through QC_metrics (


Changes in version 1.7.28:

  • Modified decomposeVar() to return statistics (but not p-values) for spike-ins when get.spikes=NA. Added block= argument for mean/variance calculations within each level of a blocking factor, followed by reporting of weighted averages (using Fisher’s method for p-values). Automatically record global statistics in the metadata of the output for use in combineVar(). Switched output to a DataFrame object for consistency with other functions.

  • Fixed testVar() to report a p-value of 1 when both the observed and null variances are zero.

  • Allowed passing of arguments to irlba() in denoisePCA() to assist convergence. Reported low-rank approximations for all genes, regardless of whether they were used in the SVD. Deprecated design= argument in favour of manual external correction of confounding effects. Supported use of a vector or DataFrame in technical= instead of a function.

  • Allowed passing of arguments to prcomp_irlba() in buildSNNGraph() to assist convergence. Allowed passing of arguments to get.knn(), switched default algorithm back to a kd-tree.

  • Added the buildKNNGraph() function to construct a simple k-nearest-neighbours graph.

  • Fixed a number of bugs in mnnCorrect(), migrated code to C++ and parallelized functions. Added variance shift adjustment, calculation of angles with the biological subspace.

  • Modified trend specification arguments in trendVar() for greater flexibility. Switched from ns() to robustSmoothSpline() to avoid bugs with unloaded predict.ns(). Added block= argument for mean/variance calculations within each level of a blocking factor.

  • Added option to avoid normalization in the SingleCellExperiment method for improvedCV2(). Switched from ns() to smooth.spline() or robustSmoothSpline() to avoid bugs.

  • Replaced zoo functions with runmed() for calculating the median trend in DM().

  • Added block= argument to correlatePairs() to calculate correlations within each level of a blocking factor. Deprecated the use of residuals=FALSE for one-way layouts in design=. Preserve input order of paired genes in the gene1/gene2 output when pairings!=NULL.

  • Added block= argument to overlapExprs() to calculate overlaps within each level of a blocking factor. Deprecated the use of residuals=FALSE for one-way layouts in design=. Switched to automatic ranking of genes based on ability to discriminate between groups. Added rank.type= and direction= arguments to control ranking of genes.

  • Modified combineVar() so that it is aware of the global stats recorded in decomposeVar(). Absence of global statistics in the input DataFrames now results in an error. Added option to method= to use Stouffer’s method with residual d.f.-weighted Z-scores. Added weighted= argument to allow weighting to be turned off for equal batch representation.

  • Modified the behaviour of min.mean= in computeSumFactors() when clusters!=NULL. Abundance filtering is now performed within each cluster and for pairs of clusters, rather than globally.

  • Switched to pairwise t-tests in findMarkers(), rather than fitting a global linear model. Added block= argument for within-block t-tests, the results of which are combined across blocks via Stouffer’s method. Added lfc= argument for testing against a log-fold change threshold. Added log.p= argument to return log-transformed p-values/FDRs. Removed empirical Bayes shrinkage as well as the min.mean= argument.

  • Added the makeTechTrend() function for generating a mean-variance trend under Poisson technical noise.

  • Added the multiBlockVar() function for convenient fitting of multiple mean-variance trends per level of a blocking factor.

  • Added the clusterModularity() function for assessing the cluster-wise modularity after graph-based clustering.

  • Added the parallelPCA() function for performing parallel analysis to choose the number of PCs.

  • Modified convertT() to return raw counts and size factors for CellDataSet output.

  • Deprecated exploreData(), selectorPlot() in favour of iSEE().


Version: 0.99.7 Category: package submission Text:


Changes in version 1.20.0:


  • seqDigest(f, "annotation/filter") works on a factor variable

  • improve the computational efficiency of seqMerge() to avoid genotype recompression by padding the 2-bit genotype array in bytes

  • significantly improve seqBlockApply() (its speed is close to seqApply())

  • reduce the overhead in seqSetFilter(, variant.sel=...)


  • seqGDS2VCF() outputs a bgzip vcf file for tabix indexing

  • two more options “Ultra” and “UltraMax” in seqStorageOption()

  • ‘@chrom_rle_val’ and ‘@chrom_rle_len’ are added to a GDS file for faster chromosome indexing

  • new function seqBCF2GDS() (requiring the software bcftools)

  • new function seqSetFilterPos()

  • new variable “$dosage_alt” in seqGetData() and seqApply()

  • import VCF files with no GT in seqVCF2GDS()

Changes in version 1.18.1-1.18.2:


  • fix an issue: seqSetFilterChrom() extends a genomic range upstream and downstream 1bp

  • use .onLoad() instead of .onAttach() to fix


Changes in version 1.2.0:


  • Add functionality for analysing VCF files containing unannotated variants

  • Add functionality for listing non-overlapping variants between profiles

  • Mitochondrial variants can now be optionally skipped when reading SNV profiles in the read_variants function

  • Add the list_variants function for listing the genotypes of user-specified variants in each provided SNV profile

  • Add the plot_variant_list function for plotting a genotype grid for each variant output by the list_variants function


  • Fix a multi-sample VCF profile creation issue (python only)

  • Reading zero-variant profiles now properly returns a GRanges object with a dummy-variant profile containing the sample name

  • Enable the plot_impacts function to properly analyse multi-impact SNVs

  • Fix reading of SNV profiles containing single-quoted strings


Changes in version 1.17.8:

  • Add method alleleCount to return count of alleles.

Changes in version 1.17.7:

  • Bug fix in alleleFrequency method for SeqVarData where frequency calculation was done twice because the first calculation was not returned.

Changes in version 1.17.6:

  • Add option to return alternate allele dosage in a sparse matrix using the Matrix package.

  • Improve speed of reading dosages by using seqBlockApply.

Changes in version 1.17.2:

  • Change implementation of iterator classes to identify indices of selected variants on object creation and store in variantList slot. All iterator classes now extend new class SeqVarIterator.


Changes in version 0.99.0:

  • New package “sevenC” for predicting chromatin looping interactions from ChIP-seq data and DNA-sequence motifs.


Changes in version 1.37:


  • (v. 1.37.2) FastqQuality() includes the last printable ASCII character ‘~’

  • (v. 1.37.3) countLines() returns numeric values, to allow for files with more than 2^31-1 lines


Changes in version 1.5.2:

  • support for generating matrices with a DNAStringSet

Changes in version 1.5.1:

  • fix GRanges list usage

  • fix conflicts of NMF:seed, by adding VariantAnnotation to Depends before NMF


Changes in version 1.5.1 (2018-03-09):

  • Added CIMLR implementation.


Changes in version 1.1.4:

  • Added the clearSpikes() function to remove all spike-in information.

  • Added the clearSizeFactors() function to remove all size factor information.

  • Added the sizeFactorNames() function to query the available (named) size factor sets.

  • isSpike() with an unknown spike-in set in type= will no longer throw an error, and will quietly return NULL.

  • isSpike<- with type=NULL is deprecated in favour of clearSpikes() for removing existing spike-in information. All spike-in sets must also be explicitly named during assignment.

  • Added the LinearEmbeddingMatrix class for storing dimensionality reduction with loadings.


Changes in version 0.99.3:

  • Consistent use of camel case throughout package

Changes in version 0.6.3:

  • Additional links to help documentation

  • Example matrices on upload page.

Changes in version 0.4.7:

  • Ability to download/reupload annotation data frame and convert annotations to factors/numerics

Changes in version 0.4.5:

  • Documentation updates to fix NOTES and pass BiocCheck


Changes in version 0.99.9:

  • remove internal keyword from generateNull

Changes in version 0.99.8:

  • vectorize getPvals

  • make toy_epxr_se

Changes in version 0.99.5:

  • represent expression data in SummarizedExperiement dataset

  • function input checkings

  • R code re-organised

Changes in version 0.99.3:

  • -change argument name bidirectional to knownDirection, default as TRUE

Changes in version 0.99.2:

  • -bidirection flag added to simpleScore() function -optimise generateNull() function -change GSEABase from import to Depends


Changes in version 1.14.0:

  • the default compression is “LZMA_RA” in snpgdsBED2GDS(), snpgdsVCF2GDS() and snpgdsVCF2GDS_R() for annotations

  • support Intel C++ compiler with SSE2/AVX2

  • allow interrupt requests in the calculation

  • new method options in snpgdsPairScore(): GVH.major, GVH.minor, GVH.major.only, GVH.minor.only

  • force to use integers for ‘snp.position’ in snpgdsCreateGeno()

  • unit tests for merging GRMs in snpgdsMergeGRM()

  • the function snpgdsSNPListStrand() is merged to snpgdsSNPListIntersect(), and it is removed from the package

  • update snpgdsSNPListIntersect() and snpgdsCombineGeno() (work correctly)

  • replace -INF by NaN in the output of snpgdsIBDKING()

Changes in version 1.12.2:

  • a new option ‘method=”Jacquard”’ in snpgdsPairIBD()

  • snpgdsGRM() can output the GRM matrix to a GDS file

  • a new function snpgdsMergeGRM() to merge multiple GRMs

Changes in version 1.12.1:

  • fix an issue in the C code ‘LENGTH or similar applied to NULL object’


Changes in version 1.0.0:

  • Package released on Bioconductor in May 2018.


Changes in version 1.13.02 (2017-11-20):

  • Eliminated C++-11 and Rcpp linking. Passing unit tests.

  • use lower_bound_ function exported by <URL:>


Changes in version 1.3.5 (2017-04-25):

  • Move scater to Imports and add scater version

  • Remove lingering references to SCESets

  • Add option to use a normal distribution for library sizes in Splat simulations

  • Allow Splat dropout parameters to be specified by experiment, batch, group or cell

  • Add SparseDC simulation

  • Rename params in metadata slot of simulation to Params for consistency

  • Improve and colourise Params print output

  • Improve test coverage

  • Various other minor updates and bug fixes


Changes in version 1.0.3:

  • Smaller bug fixes of broken unit tests through changes in 1.0.2

Changes in version 1.0.2:

  • Big memory regularly breaks the build. Thus it is no longer used by default. big memory objects can still be created manually and will be used in sponge

Changes in version 1.0.1:

  • Release with Bioconductor 3.6

  • Fix of bug caused by new version of bigmemory


Changes in version 1.10.0:


  • Add “subset” method for SummarizedExperiment objects. See

  • rowRanges() now is supported on a SummarizedExperiment object that is not a RangedSummarizedExperiment, and returns NULL. Also doing ‘rowRanges(x) <- NULL’ on a RangedSummarizedExperiment object now is supported and degrades it to a SummarizedExperiment instance.

  • Add ‘BACKEND’ argument to “realize” method for SummarizedExperiment objects.


  • saveHDF5SummarizedExperiment() and loadHDF5SummarizedExperiment() are now in the HDF5Array package.

  • Replace old “updateObject” method for SummarizedExperiment objects with a new one. The new method calls updateObject() on all the assays of the object. This will update SummarizedExperiment objects (and their derivatives like BSseq objects) that have “old” DelayedArray objects in their assays. The old method has been around since BioC 3.2 (released 2.5 years ago) and was used to update objects made prior to the change of internals that happened between BioC 3.1 and BioC 3.2. All these “old” objects should have been updated by now so we don’t need this anymore.


  • Modify the “[<-“ method for SummarizedExperiment to leave ‘metadata(x)’ intact instead of trying to combine it with ‘metadata(value)’. With this change ‘x[i , j] <- x[i , j]’ behaves like a no-op (as expected) instead of duplicating metadata(x).

  • The SummarizedExperiment() constructor does not try to downgrade the supplied rowData and/or colData to DataFrame anymore if they derive from DataFrame.


Changes in version 1.9.3:


  • removed aLFQ direct link in manual

Changes in version 1.9.2:


  • add option check_tranisitions to convert_aLFQ function

  • replace align_orig_filename column with filename

Changes in version 1.9.1:


  • SWATH2stats in BioC 3.7 development release

Changes in version 1.8.1:


  • SWATH2stats in BioC 3.6 release


Changes in version 2.3.1:

  • Partly revert 95f4094 because MSnbase:::utils.applyColumnwiseByGroup is gone.

  • Use html_document instead of html_document2 in the vignettes [2018-01-17]. # Synapter 2.1


Changes in version 1.36.0:


  • New dataset object TSExample. This dataset contains data that used to be stored in package TargetSearchData.

  • New low-level function to search peaks (FindAllPeaks). This allows advanced users to refine peak-searches.

  • New function to plot peaks across samples (plotPeakRI). Used for quality checks of peak annotation and fine-tunning search parameters.


  • Add extra checks when manipulating tsLib objects. Extra care needs to be taken if changes to the quant/selective/top masses are changed.

  • Sample IDs (names) must be unique. These might generate errors when loading old TargetSearch workspaces.


  • tsLib: ensure that every slot in the object contain a library ID.

  • Fix warnings during R CMD check.

  • Refactor C code for finding peaks. It is possible to return all peaks instead of only the most abundant. No visibles changes for the end user.

  • Refactor C code for NetCDF manipulation and peak finding to reduce code duplication. No visible changes for the end user.

  • General R code houskeeping: Removal of mixed tabs and spaces, fix tabulation, add Rbuildignore.

Changes in version 2.7.13:

  • Adding new function: PanCancerAtlas_subtypes

  • Updating DNA methylation probe information function

  • Start to update vignette

  • FPPE information is being added in GDCprepare

  • Minor issue fixes


Version: 4.0.1 Category: fixed problem with IRanges version >=2.13.28 in Text:

Version: 4.0.0 Text: package is now based on ‘GRanges’ objects instead of deprecated ‘RangedData’ objects

Version: 4.0.0 Text: vignette is now created with knitr


Changes in version 3.5:


  • Add function to parse MEME output.

  • Add parallel computing of searchSeq.

Changes in version 3.4:


  • Fix a bug in PFMSimilarity.

  • Fix an error when there are multiple classes for motif matrx.


  • readJASPARMatrix function to add the JASPAR format file.

Changes in version 3.3:


  • Adapt the runMEME to work with meme 4.10.x version.

  • Fix the scientific notation in run_MEME

  • Better error handling of MEME wrappe


Version: 099.1 Category: SIGNIFICANT USER-VISIBLE CHANGES Text: changed function behvaiour in the whole package from call-by-ref to call-by value. Adjusted accordingly all examples and the vignette.

Version: 099.1 Category: INTERNALS Text: depends now on ProtGenerics from which it uses ‘mz’

Version: 099.1 Category: INTERNALS Text: exchanged various print() with message()

Version: 099.1 Category: BUGFIXES Text:


Changes in version 1.13.2:

  • Package maintainer change: new maintainer is Ludwig Geistlinger


Changes in version 1.1.7:

  • Add mz,FragmentViews-method [2018-02-01].

  • Remove internal fragmentMass and fragmentNames functions [2018-02-22].

  • Parse “spectrumId” column of the mzML header to find the scan number (instead of the “acquisitionNum”) because ProteomDiscover generates non-standard “spectrumId” and proteowizard fails to translated it into a valid “acquisitionNum”. See #73 for details [2018-02-22].

  • Recalculate TotIonCurrent in the main loop of .readMzMl [2018-02-22].

  • Add FragmentCoverage and BondCoverage columns to bestConditions,NCBSet-method [2018-02-23].

  • Use retention times to test for correct matching between ScanHeadsman .txt output and mzML files; closes #74; [2018-02-23].

Changes in version 1.1.6:

  • Rotate fragment labels (vertical orientation) in plot [2018-01-17].

  • Replace signature for updateMedianInjectionTime,TopDownSet-method to updateMedianInjectionTime,AbstractTopDownSet-method; closes #69; see also #71 [2018-01-27].

  • Fix .matchFragments for length(fmass) == 0 [2018-01-27].

  • Just plot fragments that are present in current TopDownSet see #70 [2018-01-27].

  • Add combine,FragmentViews,FragmentViews-method [2018-01-27].

  • Allow to combine TopDownSet objects with different fragment types; closes #71 [2018-01-27].

  • Add all.equal for AbstractTopDownSet objects [2018-01-27].

  • Allow the user to decide how to handle redundant fragment matching. Current default is redundantFragmentMatch="remove" and redundantIonMatch="remove". This will reduce the number of fragment matches. Choose "closest" for both to get the old behaviour. See also #72 [2018-01-29].

  • TopDownSet object store the matching tolerance and strategies (redundantIonMatch, redundantFragmentMatch). AbstractTopDownSet and NCBSet lost their tolerance slot. Saved objects need to be recreated [2018-01-30].

  • bestConditions,NCBSet-method returns a 5-column matrix now. Colums are: Index, FragmentsAddedToCombination, BondsAddedToCombination, FragmentsInCondition, BondsInCondition; see #52 [2018-01-30].

Changes in version 1.1.5:

  • Keep full filename (before basename was used) in AbstractTopDownSet objects [2017-12-28].

  • Add plot,TopDownSet-method [2017-12-29].

  • bestConditions,NCBSet-method gains a new argument maximise that allows to optimise for number of fragments or bonds covered (default: "fragments"); see #52 [2018-01-15].

Changes in version 1.1.4:

  • Add missing export of combine and documentation [2017-12-28].

  • Resave tds example data set to reflect changes in colData introduced in version 1.1.2 [2017-12-28].

Changes in version 1.1.3:

  • Add conditionNames,AbstractTopDownSet-method to access rownames(colData(tds)) [2017-12-23].

  • Add updateConditionNames,AbstractTopDownSet-method (closes #60) [2017-12-23].

  • Turn updateMedianInjectionTime,TopDownSet-method into updateMedianInjectionTime,AbstractTopDownSet-method to work with TopDownSet and NCBSet objects [2017-12-27].

  • Add combine,AbstractTopDownSet-method to combine multiple TopDownSet/NCBSet objects (closes #69) [2017-12-28].

Changes in version 1.1.2:

  • Add .rbind to combine scan and method information with different number of colums (could happen when CID/HCD and UVPD scans are taken independently with different software versions) [2017-12-22].

  • Don’t replace NA values with zeros in the colData [2017-12-22].

  • Convert On/Off character columns in scan and method information to logical [2017-12-22].

  • Fix .camelCase to avoid “TIC” to “TIc” and “UseCalibratedUVPDTimeMs2” to “UseCalibrateduvpdTimems2” conversion (now: “Tic” and “UseCalibratedUvpdTimeMs2”) [2017-12-22].

Changes in version 1.1.1:

  • Respect assigned intensity in conditions for bestConditions,NCBSet-method and fragmentationMap (closes #62) [2017-12-02].

  • Fix explanation of random forest barchart in analysis vignette [2017-12-02].

  • Create all fragmentation methods in .readScanHeadsTable to avoid error if any is missing (fixes #68) [2017-12-20].

  • Never remove Activation column in colData (even not if readTopDownFiles(..., dropNonInformativeColumns=TRUE)) [2017-12-20].

  • Allow UVPD in fragmentationMap,NCBSet-method [2017-12-20].

  • Add new method: updateMedianInjectionTime,TopDownSet-method (closes #66) [2017-12-20].

Changes in version 1.1.0:

  • New version for Bioc 3.7 (devel) # topdownr 1.0


Changes in version 1.15.13:

  • add parameter to plotGInteractions.

Changes in version 1.15.12:

  • add new function plotGInteractions.

Changes in version 1.15.11:

  • update the title

Changes in version 1.15.10:

  • Change all “class” function to “is” function.

Changes in version 1.15.9:

  • Add lollipopData to tracks-class.

Changes in version 1.15.8:

  • Plot lollipop plot with tracks.

Changes in version 1.15.7:

  • Add new parameter rescale to lolliplot.

Changes in version 1.15.6:

  • Add new function geneTrack.

Changes in version 1.15.5:

  • fix the warning in windows documentation.

Changes in version 1.15.4:

  • fix the warning in windows documentation.

Changes in version 1.15.3:

  • fix the position of ylabs in plotOneIdeo.

Changes in version 1.15.2:

  • fix the bug in addGuideLine and viewTracks when plot tracks with breaks.

Changes in version 1.15.1:

  • fix the bug in dandelion.plot

  • use Roxygen2 to generate help documents

  • add new functions: getLocation, viewGene


Changes in version 1.1.18:

  • The plot of the differentiallyExpressed() method shows the number of clusters detected and is created by the ggplot2 package.

Changes in version 1.1.17:

  • Improved documentation.

Changes in version 1.1.7:

  • Added a new argument to the differentiallyExpressed() method, supporting the limma-trend approach for RNA-Seq.

Changes in version 1.1.6:

  • Updated GPL570 dataset.

Changes in version 1.1.3:

  • The datasets of the four species were improved to obtain a better clustering.


Changes in version 1.3.9:

  • Exporter.Rmd vignette <2017-12-13, Wed>

Changes in version 1.3.8:

  • mv treeio.Rmd vignette to Importer.Rmd and update the contents <2017-12-13, Wed>

  • write.beast for treedata object <2017-12-12, Tue>

  • add “connect” parameter in groupOTU <2017-12-12, Tue> +!msg/bioc-ggtree/Q4LnwoTf1DM/yEe95OFfCwAJ

Changes in version 1.3.7:

  • export groupClade.phylo method <2017-12-11, Mon>

Changes in version 1.3.6:

  • re-defined groupOTU and groupClade generic using S3 <2017-12-11, Mon>

Changes in version 1.3.5:

  • parent, ancestor, child, offspring, rootnode and sibling generic and method for phylo <2017-12-11, Mon>

  • update mask and merge_tree function according to the treedata object <2017-12-11, Mon>

Changes in version 1.3.4:

  • support tbl_tree object defined in tidytree <2017-12-08, Fri>

Changes in version 1.3.3:

  • read.codeml output treedata, remove codeml class and clean up code <2017-12-07, Thu>

Changes in version 1.3.2:

  • read.codeml_mlc output treedata object and remove codeml_mlc class <2017-12-06, Wed>

  • read.paml_rst output treedata and remove paml_rst class <2017-12-06, Wed>

  • read.phylip.tree and read.phylip.seq

  • read.phylip output treedata object and phylip class definition was removed

  • read.hyphy output treedata object; hyphy class definition was removed

  • remove r8s class, read.r8s now output multiPhylo object

  • jplace class inherits treedata <2017-12-05, Tue>

  • using treedata object to store beast and mrbayes tree

  • export read.mrbayes

Changes in version 1.3.1:

  • compatible to parse beast output that only contains HPD range <2017-11-01, Wed> +!msg/bioc-ggtree/RF2Ly52U_gc/jEP97nNPAwAJ


Changes in version 0.99.21 (2018-03-17):


  • Initial version


Changes in version 1.5.4 (2017-09-24):

Bug fix

  • min(ranges(GRanges)) does not seem to work anymore, replaced by more explicit expression.

  • Commented out some unit tests until subsetting of FilterRules by row and column throws an error again.


Changes in version 1.8.0:

  • Added support for StringTie output.


Version: 0.99.10 Category: NEW FEATURES Text:


Changes in version 1.99.3 (2018-01-03):

Bioconductor compliance

  • Minor modifications to comply with Bioconductor regulations

Changes in version 1.99.2 (2018-20-02):

Added RNA-seq and panel-seq capability

  • Some more minor bugfixes

Changes in version 1.99.1 (2018-12-02):

Added RNA-seq and panel-seq capability

  • Minor bugfixes

Changes in version 1.99.0 (2018-15-01):

Added RNA-seq and panel-seq capability

  • Modified the package to work with large scale RNA-seq and small scale panel-seq data

  • Please note that this might break custom libraries. In case of questions please contact the author


Changes in version 1.9.9:

  • Fix issue when package is autoloaded when starting R

Changes in version 1.9.8:

  • Fix issue where if info data.frame contained a column name “gene”, fitExtractVarPartModel() would not run

Changes in version 1.9.6:

  • Fix tximport issue with eval=FALSE

Changes in version 1.9.2:

  • Fix vignette

Changes in version 1.9.1:

  • Fix formatting of vignette

  • add description of canCorPairs() function


Changes in version 1.16:


  • Specific filtering functions have been deprecated in favor of a more general filtering mechanism.

  • Shiny-app has been rewritten.


Changes in version 3.1.3:


  • Fix misplaced parenthesis in the check for multiple spectra in findChromPeaks,OnDiskMSnExp,MSWParam. Thanks to @RonanDaly (PR #276).

  • Update link to correct metlin page in diffreport result (issue #204).

Changes in version 3.1.2:


  • Add filterFeatureDefinitions function.


  • Fix #273: better error message in case not a single feature could be defined by groupChromPeaks.

Changes in version 3.1.1:


  • Reading raw files using xcmsSet or xcmsRaw uses now the automatic file type detection feature from mzR.

  • c function to concatenate XCMSnExp objects.

  • groupnames method for XCMSnExp objects (issue #250).


  • Fix #237: findPeaks.MSW was not throwing an error if applied to multi-spectrum MS file.

  • Fix #249: quantile call in adjustRtime PeakGroups without na.rm = TRUE.

  • Fix #259


VERSION xps-1.37.2

  • file - unix line endings

VERSION xps-1.37.1

  • update INSTALL and README file

Changes in version 3.3:


Changes in version 1.1.6 (2018-04-17):

  • zinbwave now uses counts assay by default.

  • Users can now specify which assay to use to fit the zinb model.

Changes in version 1.1.5 (2018-02-15):

  • Computational weights are computed in zinbwave as saved as assay.

  • Modified vignette to include example of Differential Expression.

  • Improved documentation for zinbwave.

NEWS from new and existing Data Experiment Packages


Version: 0.99.2 Category: Fixed a few typos Text:

Version: 0.99.1 Category: Updated R version dependency from 3.4 to 3.5 Text:

Version: 0.99.0 Category: First submitted version to Bioconductor Text:

Changes in version 2.4.0:

  • Updated locus definitions based on TxDb 3.4.0 and OrgDb 3.5.0 packages

  • Remove gene expression and EHMN gene sets.


Changes in version 2.17:


  • ch2locs (retrievable via dsQTL::getSNPlocs) has been changed at about 1850 locations where rs numbers had been associated with hg19 addresses; the dsQTL regions are hg18 as are all the chr2… SNP addresses. Previously the discoverable rs numbers used in the Chicago distribution from had be mapped via SNPlocs…20111119, but now they come directly from the Chicago text file.


Changes in version 1.5.3 (2018-01-19):

User Visible Changes

  • two additional FCS files have been added: fpVac, which is useful in demonstrating gating; and fpBad, which is a very low quality file used in unit tests.


Version: 1.0.0 Text:


Changes in version 0.99.0:

  • mCSEAdata release.


Changes in version 0.99.0:


  • This is the first iteration of the MetaGxBreast package. The package contains 39 breast cancer Esets


Changes in version 0.99.0:


  • This is the first iteration of the MetaGxOvarian package. It is essentially an updated version of the curatedOvarianData package with 5 additional datasets


Changes in version 0.99.0:


  • This is the first iteration of the MetaGxPancreas package.


Changes in version 1.1.2:

  • Fix unit test error.


Changes in version 1.9.1:

  • Add vignette based on xcms3 new interface, bump minimum xcms version to 3.0.0


Changes in version 1.17.4:

  • Typo in tlopt colnames fixed for f1000 workflow <2018-04-10 Tue>

Changes in version 1.17.3:

  • Add Proteome biocView <2018-04-05 Thu>

Changes in version 1.17.2:

  • Add data from Beltran et al. 2016 <2018-03-17 Sat>

  • Add data from Hirst et al. 2018 <2018-03-18 Sun>

  • Add data from Itzhal et al. 2017 <2018-03-20 Tue>

Changes in version 1.17.1:

  • Update README with information on how to add data <2018-03-08 Thu>


Changes in version 2016-04-21:

  • Initial release for Bioconductor


Changes in version 0.99.7:

  • Motif rankings are now transposed (motifs in rows, genes in columns), and updated to motif collection 9.

  • Motif-TF annotation databases have been re-formatted for easier selection of the direct/inferred annotations.


Changes in version 1.17.1:

  • Fix/update vignettes <2018-01-12 Fri>

  • Add mention of DEP package <2018-01-13 Sat>

Changes in version 1.17.0:

  • New Bioc devel version

Changes in version 1.16.0:

  • New Bioc release version


Changes in version 1.17.2:


  • The dataset TargetSearchData which used to contain TargetSearch objects has been moved from package TargetSearchData to package TargetSearch. Note that the dataset name has been renamed to TSExample. To load it use data(TSExample) within TargetSearch.


Changes in version 0.99.3:

  • changing unit tests

Changes in version 0.99.2:

  • changing man page example

Changes in version 0.99.1:

  • changes to comply with Bioconductor package guide lines

Changes in version 0.99.0:

  • First release


Changes in version 1.1.1:

  • Add UVPD data for CA.

Changes in version 1.1.0:

  • New version for Bioc 3.7 (devel) # topdownrdata 1.0

Deprecated and Defunct Packages

Nine software packages were removed from this release (after being deprecated in BioC 3.6): BioMedR, ddgraph, EWCE, HCsnip, stepwiseCM, domainsignatures, iontree, oneChannelGUI, RCytoscape. One software package was removed from Bioconductor at user request (mvGST) without previous deprecation.

Ten software packages (ontoCat, spliceR, GMRP, MBttest, OperaMate, DASC, htSeqTools, PAnnBuilder, phenoDist, BrowserVizDemo) are deprecated in this release and will be removed in BioC 3.8.

One annotation data package (IlluminaHumanMethylation450k.db) was removed from this release.

Three experimental data packages (RnaSeqTutorial, cheung2010, MEALData) are deprecated in this release and will be removed in Bioc 3.8.