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Oct 31, 2018


We are pleased to announce Bioconductor 3.8, consisting of 1649 software packages, 360 experiment data packages, 941 annotation packages, and 23 workflows.

There are 95 new software packages, 21 new data experiment packages, 2 new workflows, and many updates and improvements to existing packages; Bioconductor 3.8 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 3.8

To update to or install Bioconductor 3.8:

  1. Install R >=3.5.0. Bioconductor 3.8 has been designed expressly for this version of R.

  2. Follow the instructions at

New Software Packages

There are 95 new software packages in this release of Bioconductor.

  • abseqR AbSeq is a comprehensive bioinformatic pipeline for the analysis of sequencing datasets generated from antibody libraries and abseqR is one of its packages. abseqR empowers the users of abseqPy ( with plotting and reporting capabilities and allows them to generate interactive HTML reports for the convenience of viewing and sharing with other researchers. Additionally, abseqR extends abseqPy to compare multiple repertoire analyses and perform further downstream analysis on its output.

  • ACE Uses segmented copy number data to estimate tumor cell percentage and produce copy number plots displaying absolute copy numbers.

  • AffiXcan Impute a GReX (Genetically Regulated Expression) for a set of genes in a sample of individuals, using a method based on the Total Binding Affinity (TBA). Statistical models to impute GReX can be trained with a training dataset where the real total expression values are known.

  • appreci8R The appreci8R is an R version of our appreci8-algorithm - A Pipeline for PREcise variant Calling Integrating 8 tools. Variant calling results of our standard appreci8-tools (GATK, Platypus, VarScan, FreeBayes, LoFreq, SNVer, samtools and VarDict), as well as up to 5 additional tools is combined, evaluated and filtered.

  • artMS artMS provides a set of tools for the analysis of proteomics label-free datasets. It takes as input the MaxQuant search result output (evidence.txt file) and performs quality control, relative quantification using MSstats, downstream analysis and integration. artMS also provides a set of functions to re-format and make it compatible with other analytical tools, including, SAINTq, SAINTexpress, Phosfate, and PHOTON.

  • AssessORF In order to assess the quality of a set of predicted genes for a genome, evidence must first be mapped to that genome. Next, each gene must be categorized based on how strong the evidence is for or against that gene. The AssessORF package provides the functions and class structures necessary for accomplishing those tasks, using proteomic hits and evolutionarily conserved start codons as the forms of evidence.

  • bayNorm bayNorm is used for normalizing single-cell RNA-seq data.

  • BDMMAcorrect Metagenomic sequencing techniques enable quantitative analyses of the microbiome. However, combining the microbial data from these experiments is challenging due to the variations between experiments. The existing methods for correcting batch effects do not consider the interactions between variables—microbial taxa in microbial studies—and the overdispersion of the microbiome data. Therefore, they are not applicable to microbiome data. We develop a new method, Bayesian Dirichlet-multinomial regression meta-analysis (BDMMA), to simultaneously model the batch effects and detect the microbial taxa associated with phenotypes. BDMMA automatically models the dependence among microbial taxa and is robust to the high dimensionality of the microbiome and their association sparsity.

  • BiocNeighbors Implements exact and approximate methods for nearest neighbor detection, in a framework that allows them to be easily switched within Bioconductor packages or workflows. The exact algorithm is implemented using pre-clustering with the k-means algorithm, as described by Wang (2012). This is faster than conventional kd-trees for neighbor searching in higher (> 20) dimensional data. The approximate method uses the Annoy algorithm. Functions are also provided to search for all neighbors within a given distance. Parallelization is achieved for all methods using the BiocParallel framework.

  • BiocPkgTools Bioconductor has a rich ecosystem of metadata around packages, usage, and build status. This package is a simple collection of functions to access that metadata from R. The goal is to expose metadata for data mining and value-added functionality such as package searching, text mining, and analytics on packages.

  • brainImageR BrainImageR is a package that provides the user with information of where in the human brain their gene set corresponds to. This is provided both as a continuous variable and as a easily-interpretable image. BrainImageR has additional functionality of identifying approximately when in developmental time that a gene expression dataset corresponds to. Both the spatial gene set enrichment and the developmental time point prediction are assessed in comparison to the Allen Brain Atlas reference data.

  • breakpointR This package implements functions for finding breakpoints, plotting and export of Strand-seq data.

  • BUScorrect High-throughput experimental data are accumulating exponentially in public databases. However, mining valid scientific discoveries from these abundant resources is hampered by technical artifacts and inherent biological heterogeneity. The former are usually termed “batch effects,” and the latter is often modelled by “subtypes.” The R package BUScorrect fits a Bayesian hierarchical model, the Batch-effects-correction-with-Unknown-Subtypes model (BUS), to correct batch effects in the presence of unknown subtypes. BUS is capable of (a) correcting batch effects explicitly, (b) grouping samples that share similar characteristics into subtypes, (c) identifying features that distinguish subtypes, and (d) enjoying a linear-order computation complexity.

  • CAMTHC An R package for tissue heterogeneity characterization by convex analysis of mixtures (CAM). It provides basic functions to perform unsupervised deconvolution on mixture expression profiles by CAM and some auxiliary functions to help understand the subpopulation-specific results. It also implements functions to perform supervised deconvolution based on prior knowledge of molecular markers, S matrix or A matrix. Combining molecular markers from CAM and from prior knowledge can achieve semi-supervised deconvolution of mixtures.

  • celaref After the clustering step of a single-cell RNAseq experiment, this package aims to suggest labels/cell types for the clusters, on the basis of similarity to a reference dataset. It requires a table of read counts per cell per gene, and a list of the cells belonging to each of the clusters, (for both test and reference data).

  • CellTrails CellTrails is an unsupervised algorithm for the de novo chronological ordering, visualization and analysis of single-cell expression data. CellTrails makes use of a geometrically motivated concept of lower-dimensional manifold learning, which exhibits a multitude of virtues that counteract intrinsic noise of single cell data caused by drop-outs, technical variance, and redundancy of predictive variables. CellTrails enables the reconstruction of branching trajectories and provides an intuitive graphical representation of expression patterns along all branches simultaneously. It allows the user to define and infer the expression dynamics of individual and multiple pathways towards distinct phenotypes.

  • cicero Cicero computes putative cis-regulatory maps from single-cell chromatin accessibility data. It also extends monocle 2 for use in chromatin accessibility data.

  • COCOA COCOA is a method for understanding variation among samples and can be used with data that includes genomic coordinates such as DNA methylation. On a high level, COCOA uses a database of “region sets” and principal component analysis (PCA) of your data to identify sources of variation among samples. A region set is a set of genomic regions that share a biological annotation, for instance, transcription factor binding regions, histone modification regions, or open chromatin regions. COCOA works in both supervised (known groups of samples) and unsupervised (no groups) situations and can be used as a complement to “differential” methods that find discrete differences between groups. COCOA can identify biologically meaningful sources of variation between samples and increase understanding of variation in your data.

  • compartmap Compartmap performs shrunken A/B compartment inference from ATAC-seq and methylation arrays.

  • condcomp For a given clustered data, which can also be split into two conditions, this package provides a way to perform a condition comparison on said clustered data. The comparison is performed on each cluster. Several statistics are used and, when analysed in conjunction, they might give some insight regarding the heterogeneity of some of the clusters.

  • consensus An implementation of the American Society for Testing and Materials (ASTM) Standard E691 for interlaboratory testing procedures, designed for cross-platform genomic measurements. Given three (3) or more genomic platforms or laboratory protocols, this package provides interlaboratory testing procedures giving per-locus comparisons for sensitivity and precision between platforms.

  • consensusDE This package allows users to perform DE analysis using multiple algorithms. It seeks consensus from multiple methods. Currently it supports “Voom”, “EdgeR” and “DESeq”, but can be easily extended. It uses RUV-seq (optional) to remove batch effects.

  • coRdon Tool for analysis of codon usage in various unannotated or KEGG/COG annotated DNA sequences. Calculates different measures of CU bias and CU-based predictors of gene expressivity, and performs gene set enrichment analysis for annotated sequences. Implements several methods for visualization of CU and enrichment analysis results.

  • countsimQC countsimQC provides functionality to create a comprehensive report comparing a broad range of characteristics across a collection of count matrices. One important use case is the comparison of one or more synthetic count matrices to a real count matrix, possibly the one underlying the simulations. However, any collection of count matrices can be compared.

  • cTRAP Compare differential gene expression results with those from known cellular perturbations (such as gene knock-down, overexpression or small molecules) derived from the Connectivity Map. Such analyses allow not only to infer the molecular causes of the observed difference in gene expression but also to identify small molecules that could drive or revert specific transcriptomic alterations.

  • DEqMS DEqMS is developped on top of Limma. However, Limma assumes same prior variance for all genes. In proteomics, the accuracy of protein abundance estimates varies by the number of peptides/PSMs quantified in both label-free and labelled data. Proteins quantification by multiple peptides or PSMs are more accurate. DEqMS package is able to estimate different prior variances for proteins quantified by different number of PSMs/peptides, therefore acchieving better accuracy. The package can be applied to analyze both label-free and labelled proteomics data.

  • EnhancedVolcano Volcano plots represent a useful way to visualise the results of differential expression analyses. Here, we present a highly-configurable function that produces publication-ready volcano plots. EnhancedVolcano will attempt to fit as many transcript names in the plot window as possible, thus avoiding ‘clogging’ up the plot with labels that could not otherwise have been read.

  • ERSSA The ERSSA package takes user supplied RNA-seq differential expression dataset and calculates the number of differentially expressed genes at varying biological replicate levels. This allows the user to determine, without relying on any a priori assumptions, whether sufficient differential detection has been acheived with their RNA-seq dataset.

  • ExCluster ExCluster flattens Ensembl and GENCODE GTF files into GFF files, which are used to count reads per non-overlapping exon bin from BAM files. This read counting is done using the function featureCounts from the package Rsubread. Library sizes are normalized across all biological replicates, and ExCluster then compares two different conditions to detect signifcantly differentially spliced genes. This process requires at least two independent biological repliates per condition, and ExCluster accepts only exactly two conditions at a time. ExCluster ultimately produces false discovery rates (FDRs) per gene, which are used to detect significance. Exon log2 fold change (log2FC) means and variances may be plotted for each significantly differentially spliced gene, which helps scientists develop hypothesis and target differential splicing events for RT-qPCR validation in the wet lab.

  • FastqCleaner An interactive web application for quality control, filtering and trimming of FASTQ files. This user-friendly tool combines a pipeline for data processing based on Biostrings and ShortRead infrastructure, with a cutting-edge visual environment. Single-Read and Paired-End files can be locally processed. Diagnostic interactive plots (CG content, per-base sequence quality, etc.) are provided for both the input and output files.

  • FCBF This package provides a simple R implementation for the Fast Correlation Based Filter described in Yu, L. and Liu, H.; Feature Selection for High-Dimensional Data: A Fast Correlation Based Filter Solution,Proc. 20th Intl. Conf. Mach. Learn. (ICML-2003), Washington DC, 2003 The current package is an intent to make easier for bioinformaticians to use FCBF for feature selection, especially regarding transcriptomic data.This implies discretizing expression (function discretize_exprs) before calculating the features that explain the class, but are not predictable by other features. The functions are implemented based on the algorithm of Yu and Liu, 2003 and Rajarshi Guha’s implementation from 13/05/2005 available (as of 26/08/2018) at .

  • FoldGO FoldGO is a package designed to annotate gene sets derived from expression experiments and identify fold-change-specific GO terms.

  • GeneAccord A statistical framework to examine the combinations of clones that co-exist in tumors. More precisely, the algorithm finds pairs of genes that are mutated in the same tumor but in different clones, i.e. their subclonal mutation profiles are mutually exclusive. We refer to this as clonally exclusive. It means that the mutations occurred in different branches of the tumor phylogeny, indicating parallel evolution of the clones. Our statistical framework assesses whether a pattern of clonal exclusivity occurs more often than expected by chance alone across a cohort of patients. The required input data are the mutated gene-to-clone assignments from a cohort of cancer patients, which were obtained by running phylogenetic tree inference methods. Reconstructing the evolutionary history of a tumor and detecting the clones is challenging. For nondeterministic algorithms, repeated tree inference runs may lead to slightly different mutation-to-clone assignments. Therefore, our algorithm was designed to allow the input of multiple gene-to-clone assignments per patient. They may have been generated by repeatedly performing the tree inference, or by sampling from the posterior distribution of trees. The tree inference methods designate the mutations to individual clones. The mutations can then be mapped to genes or pathways. Hence our statistical framework can be applied on the gene level, or on the pathway level to detect clonally exclusive pairs of pathways. If a pair is significantly clonally exclusive, it points towards the fact that this specific clone configuration confers a selective advantage, possibly through synergies between the clones with these mutations.

  • GIGSEA We presented the Genotype-imputed Gene Set Enrichment Analysis (GIGSEA), a novel method that uses GWAS-and-eQTL-imputed trait-associated differential gene expression to interrogate gene set enrichment for the trait-associated SNPs. By incorporating eQTL from large gene expression studies, e.g. GTEx, GIGSEA appropriately addresses such challenges for SNP enrichment as gene size, gene boundary, SNP distal regulation, and multiple-marker regulation. The weighted linear regression model, taking as weights both imputation accuracy and model completeness, was used to perform the enrichment test, properly adjusting the bias due to redundancy in different gene sets. The permutation test, furthermore, is used to evaluate the significance of enrichment, whose efficiency can be largely elevated by expressing the computational intensive part in terms of large matrix operation. We have shown the appropriate type I error rates for GIGSEA (<5%), and the preliminary results also demonstrate its good performance to uncover the real signal.

  • glmSparseNet glmSparseNet is an R-package that generalizes sparse regression models when the features (e.g. genes) have a graph structure (e.g. protein-protein interactions), by including network-based regularizers. glmSparseNet uses the glmnet R-package, by including centrality measures of the network as penalty weights in the regularization. The current version implements regularization based on node degree, i.e. the strength and/or number of its associated edges, either by promoting hubs in the solution or orphan genes in the solution. All the glmnet distribution families are supported, namely “gaussian”, “poisson”, “binomial”, “multinomial”, “cox”, and “mgaussian”.

  • gpart we provide a new SNP sequence partitioning method which partitions the whole SNP sequence based on not only LD block structures but also gene location information. The LD block construction for GPART is performed using Big-LD algorithm, with additional improvement from previous version reported in Kim et al.(2017). We also add a visualization tool to show the LD heatmap with the information of LD block boundaries and gene locations in the package.

  • gwasurvivr gwasurvivr is a package to perform survival analysis using Cox proportional hazard models on imputed genetic data.

  • HiCBricks A flexible framework for storing and accessing high-resolution Hi-C data through HDF files. HiCBricks allows import of Hi-C data through various formats such as the 2D matrix format or a generalized n-column table formats. In terms of access, HiCBricks offers functions to retrieve values from genomic loci separated by a certain distance, or the ability to fetch matrix subsets using word alike terms. HiCBricks will at a later point offer the ability to fetch multiple matrix subsets using fewer calls. It offers the capacity to store GenomicRanges that may be associated to a particular Hi-C experiment, to do basic ranges overlap (any, within) with the Hi-C experiment associated Ranges object and also to store any metadata that users may think to be relevant for their Hi-C experiment. Finally, you can do TAD calls with LSD and create pretty heatmaps.

  • hierinf Tools to perform hierarchical inference for one or multiple studies / data sets based on high-dimensional multivariate (generalised) linear models. A possible application is to perform hierarchical inference for GWA studies to find significant groups or single SNPs (if the signal is strong) in a data-driven and automated procedure. The method is based on an efficient hierarchical multiple testing correction and controls the FWER. The functions can easily be run in parallel.

  • HIREewas In epigenome-wide association studies, the measured signals for each sample are a mixture of methylation profiles from different cell types. The current approaches to the association detection only claim whether a cytosine-phosphate-guanine (CpG) site is associated with the phenotype or not, but they cannot determine the cell type in which the risk-CpG site is affected by the phenotype. We propose a solid statistical method, HIgh REsolution (HIRE), which not only substantially improves the power of association detection at the aggregated level as compared to the existing methods but also enables the detection of risk-CpG sites for individual cell types. The “HIREewas” R package is to implement HIRE model in R.

  • HPAanalyze Provide functions for retrieving, exploratory analyzing and visualizing the Human Protein Atlas data.

  • iasva Iteratively Adjusted Surrogate Variable Analysis (IA-SVA) is a statistical framework to uncover hidden sources of variation even when these sources are correlated. IA-SVA provides a flexible methodology to i) identify a hidden factor for unwanted heterogeneity while adjusting for all known factors; ii) test the significance of the putative hidden factor for explaining the unmodeled variation in the data; and iii), if significant, use the estimated factor as an additional known factor in the next iteration to uncover further hidden factors.

  • icetea icetea (Integrating Cap Enrichment with Transcript Expression Analysis) provides functions for end-to-end analysis of multiple 5’-profiling methods such as CAGE, RAMPAGE and MAPCap, beginning from raw reads to detection of transcription start sites using replicates. It also allows performing differential TSS detection between group of samples, therefore, integrating the mRNA cap enrichment information with transcript expression analysis.

  • INDEED An Implementation of Integrated Differential Expression and Differential Network Analysis of Omic Data. The differential network is obtained based on partial correlation or correlation.

  • ipdDb All alleles from the IPD IMGT/HLA and IPD KIR database for Homo sapiens. Reference: Robinson J, Maccari G, Marsh SGE, Walter L, Blokhuis J, Bimber B, Parham P, De Groot NG, Bontrop RE, Guethlein LA, and Hammond JA KIR Nomenclature in non-human species Immunogenetics (2018), in preparation.

  • IsoCorrectoR IsoCorrectoR is a tool for correcting natural isotope abundance contributions in tracing experiments.

  • KinSwingR KinSwingR integrates phosphosite data derived from mass-spectrometry data and kinase-substrate predictions to predict kinase activity. Several functions allow the user to build PWM models of kinase-subtrates, statistically infer PWM:substrate matches, and integrate these data to infer kinase activity.

  • levi The tool integrates data from biological networks with transcriptomes, displaying a heatmap with surface curves to evidence the altered regions.

  • LoomExperiment The LoomExperiment class provide a means to easily convert Bioconductor’s “Experiment” classes to loom files and vice versa.

  • LRBaseDbi Interface to construct LRBase package (

  • maser This package provides functionalities for analysis, annotation and visualizaton of alternative splicing events.

  • methylGSA The main functions for methylGSA are methylglm and methylRRA. methylGSA implements logistic regression adjusting number of probes as a covariate. methylRRA adjusts multiple p-values of each gene by Robust Rank Aggregation. For more detailed help information, please see the vignette.

  • MetID This package uses an innovative network-based approach that will enhance our ability to determine the identities of significant ions detected by LC-MS.

  • MetNet MetNet contains functionality to infer metabolic network topologies from quantitative data and high-resolution mass/charge information. Using statistical models (including correlation, mutual information, regression and Bayes statistics) and quantitative data (intensity values of features) adjacency matrices are inferred that can be combined to a consensus matrix. Mass differences calculated between mass/charge values of features will be matched against a data frame of supplied mass/charge differences referring to transformations of enzymatic activities. In a third step, the two matrices are combined to form a adjacency matrix inferred from both quantitative and structure information.

  • miRSM The package aims to identify miRNA sponge modules by integrating expression data and miRNA-target binding information. It provides several functions to study miRNA sponge modules, including popular methods for inferring gene modules (candidate miRNA sponge modules), and a function to identify miRNA sponge modules, as well as a function to conduct functional analysis of miRNA sponge modules.

  • mixOmics Multivariate methods are well suited to large omics data sets where the number of variables (e.g. genes, proteins, metabolites) is much larger than the number of samples (patients, cells, mice). They have the appealing properties of reducing the dimension of the data by using instrumental variables (components), which are defined as combinations of all variables. Those components are then used to produce useful graphical outputs that enable better understanding of the relationships and correlation structures between the different data sets that are integrated. mixOmics offers a wide range of multivariate methods for the exploration and integration of biological datasets with a particular focus on variable selection. The package proposes several sparse multivariate models we have developed to identify the key variables that are highly correlated, and/or explain the biological outcome of interest. The data that can be analysed with mixOmics may come from high throughput sequencing technologies, such as omics data (transcriptomics, metabolomics, proteomics, metagenomics etc) but also beyond the realm of omics (e.g. spectral imaging). The methods implemented in mixOmics can also handle missing values without having to delete entire rows with missing data. A non exhaustive list of methods include variants of generalised Canonical Correlation Analysis, sparse Partial Least Squares and sparse Discriminant Analysis. Recently we implemented integrative methods to combine multiple data sets: N-integration with variants of Generalised Canonical Correlation Analysis and P-integration with variants of multi-group Partial Least Squares.

  • mlm4omics To conduct Bayesian inference regression for responses with multilevel explanatory variables and missing values; It uses function from ‘Stan’, a software to implement posterior sampling using Hamiltonian MC and its variation Non-U-Turn algorithms. It implements the posterior sampling of regression coefficients from the multilevel regression models. The package has two main functions to handle not-missing-at-random missing responses and left-censored with not-missing-at random responses. The purpose is to provide a similar format as the other R regression functions but using ‘Stan’ models.

  • MPRAnalyze MPRAnalyze provides statistical framework for the analysis of data generated by Massively Parallel Reporter Assays (MPRAs), used to directly measure enhancer activity. MPRAnalyze can be used for quantification of enhancer activity, classification of active enhancers and comparative analyses of enhancer activity between conditions. MPRAnalyze construct a nested pair of generalized linear models (GLMs) to relate the DNA and RNA observations, easily adjustable to various experimental designs and conditions, and provides a set of rigorous statistical testig schemes.

  • MSstatsTMT Tools for protein significance analysis in shotgun mass spectrometry-based proteomic experiments with tandem mass tag (TMT) labeling.

  • MTseeker Variant analysis tools for mitochondrial genetics.

  • multiHiCcompare multiHiCcompare provides functions for joint normalization and difference detection in multiple Hi-C datasets. This extension of the original HiCcompare package now allows for Hi-C experiments with more than 2 groups and multiple samples per group. multiHiCcompare operates on processed Hi-C data in the form of sparse upper triangular matrices. It accepts four column (chromosome, region1, region2, IF) tab-separated text files storing chromatin interaction matrices. multiHiCcompare provides cyclic loess and fast loess (fastlo) methods adapted to jointly normalizing Hi-C data. Additionally, it provides a general linear model (GLM) framework adapting the edgeR package to detect differences in Hi-C data in a distance dependent manner.

  • NBSplice The package proposes a differential splicing evaluation method based on isoform quantification. It applies generalized linear models with negative binomial distribution to infer changes in isoform relative expression.

  • NeighborNet Identify the putative mechanism explaining the active interactions between genes in the investigated phenotype.

  • NormalyzerDE NormalyzerDE provides screening of normalization methods for LC-MS based expression data. It calculates a range of normalized matrices using both existing approaches and a novel time-segmented approach, calculates performance measures and generates an evaluation report. Furthermore, it provides an easy utility for Limma- or ANOVA- based differential expression analysis.

  • nuCpos nuCpos, a derivative of NuPoP, is an R package for prediction of nucleosome positions. In nuCpos, a duration hidden Markov model is trained with a chemical map of nucleosomes either from budding yeast, fission yeast, or mouse embryonic stem cells. nuCpos outputs the Viterbi (most probable) path of nucleosome-linker states, predicted nucleosome occupancy scores and histone binding affinity (HBA) scores as NuPoP does. nuCpos can also calculate local and whole nucleosomal HBA scores for a given 147-bp sequence. Furthermore, effect of genetic alterations on nucleosome occupancy can be predicted with this package. The parental package NuPoP, which is based on an MNase-seq-based map of budding yeast nucleosomes, was developed by Ji-Ping Wang and Liqun Xi, licensed under GPL-2.

  • OMICsPCA OMICsPCA is an analysis pipeline designed to integrate multi OMICs experiments done on various subjects (e.g. Cell lines, individuals), treatments (e.g. disease/control) or time points and to analyse such integrated data from various various angles and perspectives. In it’s core OMICsPCA uses Principal Component Analysis (PCA) to integrate multiomics experiments from various sources and thus has ability to over data insufficiency issues by using the ingegrated data as representatives. OMICsPCA can be used in various application including analysis of overall distribution of OMICs assays across various samples /individuals /time points; grouping assays by user-defined conditions; identification of source of variation, similarity/dissimilarity between assays, variables or individuals.

  • onlineFDR This package allows users to control the false discovery rate for online hypothesis testing, where hypotheses arrive sequentially in a stream, as presented by Javanmard and Montanari (2015, 2018). In this framework, a null hypothesis is rejected based only on the previous decisions, as the future p-values and the number of hypotheses to be tested are unknown.

  • OUTRIDER Identification of aberrent gene expression in RNA-seq data. Read count expectations are modeled by an autoencoder to control for confounders in the data. Given these expectations, the RNA-seq read counts are assumed to follow a negative binomial distribution with a gene-specific dispersion. Outliers are then identified as read counts that significantly deviate from this distribution. Further OUTRIDER provides useful plotting function to analyze and visualize the results.

  • PepsNMR This package provides R functions for common pre-procssing steps that are applied on 1H-NMR data. It also provides a function to read the FID signals directly in the Bruker format.

  • plotGrouper A shiny app-based GUI wrapper for ggplot with built-in statistical analysis. Import data from file and use dropdown menus and checkboxes to specify the plotting variables, graph type, and look of your plots. Once created, plots can be saved independently or stored in a report that can be saved as a pdf. If new data are added to the file, the report can be refreshed to include new data. Statistical tests can be selected and added to the graphs. Analysis of flow cytometry data is especially integrated with plotGrouper. Count data can be transformed to return the absolute number of cells in a sample (this feature requires inclusion of the number of beads per sample and information about any dilution performed).

  • primirTSS A fast, convenient tool to identify the TSSs of miRNAs by integrating the data of H3K4me3 and Pol II as well as combining the conservation level and sequence feature, provided within both command-line and graphical interfaces, which achieves a better performance than the previous non-cell-specific methods on miRNA TSSs.

  • ProteoMM ProteoMM is a statistical method to perform model-based peptide-level differential expression analysis of single or multiple datasets. For multiple datasets ProteoMM produces a single fold change and p-value for each protein across multiple datasets. ProteoMM provides functionality for normalization, missing value imputation and differential expression. Model-based peptide-level imputation and differential expression analysis component of package follows the analysis described in “A statistical framework for protein quantitation in bottom-up MS based proteomics” (Karpievitch et al. Bioinformatics 2009). EigenMS normalisation is implemented as described in “Normalization of peak intensities in bottom-up MS-based proteomics using singular value decomposition.” (Karpievitch et al. Bioinformatics 2009).

  • qPLEXanalyzer Tools for quantitative proteomics data analysis generated from qPLEX-RIME method.

  • QSutils Set of utility functions for viral quasispecies analysis with NGS data. Most functions are equally useful for metagenomic studies. There are three main types: (1) data manipulation and exploration—functions useful for converting reads to haplotypes and frequencies, repairing reads, intersecting strand haplotypes, and visualizing haplotype alignments. (2) diversity indices—functions to compute diversity and entropy, in which incidence, abundance, and functional indices are considered. (3) data simulation—functions useful for generating random viral quasispecies data.

  • REBET There is an increasing focus to investigate the association between rare variants and diseases. The REBET package implements the subREgion-based BurdEn Test which is a powerful burden test that simultaneously identifies susceptibility loci and sub-regions.

  • Rmmquant RNA-Seq is currently used routinely, and it provides accurate information on gene transcription. However, the method cannot accurately estimate duplicated genes expression. Several strategies have been previously used, but all of them provide biased results. With Rmmquant, if a read maps at different positions, the tool detects that the corresponding genes are duplicated; it merges the genes and creates a merged gene. The counts of ambiguous reads is then based on the input genes and the merged genes. Rmmquant is a drop-in replacement of the widely used tools findOverlaps and featureCounts that handles multi-mapping reads in an unabiased way.

  • RNASeqR This R package is designed for case-control RNA-Seq analysis (two-group). There are six steps: “RNASeqRParam S4 Object Creation”, “Environment Setup”, “Quality Assessment”, “Reads Alignment & Quantification”, “Gene-level Differential Analyses” and “Functional Analyses”. Each step corresponds to a function in this package. After running functions in order, a basic RNASeq analysis would be done easily.

  • SCBN This package provides a scale based normalization (SCBN) method to identify genes with differential expression between different species. It takes into account the available knowledge of conserved orthologous genes and the hypothesis testing framework to detect differentially expressed orthologous genes. The method on this package are described in the article ‘A statistical normalization method and differential expression analysis for RNA-seq data between different species’ by Yan Zhou, Jiadi Zhu, Tiejun Tong, Junhui Wang, Bingqing Lin, Jun Zhang (2018, pending publication).

  • scruff A pipeline which processes single cell RNA-seq (scRNA-seq) reads from CEL-seq and CEL-seq2 protocols. Demultiplex scRNA-seq FASTQ files, align reads to reference genome using Rsubread, and generate UMI filtered count matrix. Also provide visualizations of read alignments and pre- and post-alignment QC metrics.

  • sesame Tools For analyzing Illumina Infinium DNA methylation arrays.

  • sigFeature This package provides a novel feature selection algorithm for binary classification using support vector machine recursive feature elimination SVM-RFE and t-statistic. In this feature selection process, the selected features are differentially significant between the two classes and also they are good classifier with higher degree of classification accuracy.

  • SIMD This package provides a inferential analysis method for detecting differentially expressed CpG sites in MeDIP-seq data. It uses statistical framework and EM algorithm, to identify differentially expressed CpG sites. The methods on this package are described in the article ‘Methylation-level Inferences and Detection of Differential Methylation with Medip-seq Data’ by Yan Zhou, Jiadi Zhu, Mingtao Zhao, Baoxue Zhang, Chunfu Jiang and Xiyan Yang (2018, pending publication).

  • slingshot Provides functions for inferring continuous, branching lineage structures in low-dimensional data. Slingshot was designed to model developmental trajectories in single-cell RNA sequencing data and serve as a component in an analysis pipeline after dimensionality reduction and clustering. It is flexible enough to handle arbitrarily many branching events and allows for the incorporation of prior knowledge through supervised graph construction.

  • slinky Wrappers to query the L1000 metadata available via the REST API as well as helpers for dealing with LINCS gctx files, extracting data sets of interest, converting to SummarizedExperiment objects, and some facilities for performing streamlined differential expression analysis of these data sets.

  • sparsenetgls The package provides methods of combining the graph structure learning and generalized least squares regression to improve the regression estimation. The main function sparsenetgls() provides solutions for multivariate regression with Gaussian distributed dependant variables and explanatory variables utlizing multiple well-known graph structure learning approaches to estimating the precision matrix, and uses a penalized variance covariance matrix with a distance tuning parameter of the graph structure in deriving the sandwich estimators in generalized least squares (gls) regression. This package also provides functions for assessing a Gaussian graphical model which uses the penalized approach. It uses Receiver Operative Characteristics curve as a visualization tool in the assessment.

  • strandCheckR This package aims to quantify and remove putative double strand DNA from a strand-specific RNA sample. There are also options and methods to plot the positive/negative proportions of all sliding windows, which allow users to have an idea of how much the sample was contaminated and the appropriate threshold to be used for filtering.

  • TimeSeriesExperiment Visualization and analysis toolbox for short time course data which includes dimensionality reduction, clustering, two-sample differential expression testing and gene ranking techniques. The package also provides methods for retrieving enriched pathways.

  • transite transite is a computational method that allows comprehensive analysis of the regulatory role of RNA-binding proteins in various cellular processes by leveraging preexisting gene expression data and current knowledge of binding preferences of RNA-binding proteins.

  • tRNA The tRNA package allows tRNA sequences and structures to be accessed and used for subsetting. In addition, it provides visualization tools to compare feature parameters of multiple tRNA sets and correlate them to additional data. The tRNA package uses GRanges objects as inputs requiring only few additional column data sets.

  • tRNAdbImport tRNAdbImport imports the entries of the tRNAdb and mtRNAdb ( as GRanges object.

  • tximeta Transcript quantification import from Salmon with automatic population of metadata and transcript ranges. Filtered, combined, or de novo transcriptomes can be linked to the appropriate sources with linkedTxomes and shared for reproducible analyses.

  • Ularcirc Ularcirc reads in STAR aligned splice junction files and provides visualisation and analysis tools for splicing analysis. Users can assess backsplice junctions and forward canonical junctions.

  • universalmotif Allows for importing most common motif types into R for use by functions provided by other Bioconductor motif-related packages. Motifs can be exported into most major motif formats from various classes as defined by other Bioconductor packages. A suite of motif and sequence manipulation and analysis functions are included, including enrichment, comparison, P-value calculation, shuffling, trimming, higher-order motifs, and others.

  • Wrench Wrench is a package for normalization sparse genomic count data, like that arising from 16s metagenomic surveys.

  • XINA An intuitive R package simplifies network analyses output from multiplexed high-dimensional proteomics/trascriptomics kinetics data.

New Data Experiment Packages

There are 21 new data experiment packages in this release of Bioconductor.

  • allenpvc Celular taxonomy of the primary visual cortex in adult mice based on single cell RNA-sequencing from a study performed by the Allen Institute for Brain Science. In said study 49 transcriptomic cell types are identified.

  • AssessORFData This package provides access to mapping and results objects generated by the AssessORF package, as well as the genome sequences for the strains corresponding to those objects.

  • brainImageRdata brainImageRdata contains image masks for the developing human and the adult human brain. These masks can be used in conjunction with the gene expression data to generate spatial gene set enrichment plots. It also contains the expression data for the 15 pcw human brain, the adult human brain, and the developing human brain.

  • breakpointRdata Strand-seq data to demonstrate functionalities of breakpointR package.

  • celarefData This experiment data contains some processed data used in the celaref package vignette. These are publically available datasets, that have been processed by celaref package, and can be manipulated further with it.

  • CopyNeutralIMA Provides a set of genomic copy neutral samples hybridized using Illumina Methylation arrays (450k and EPIC).

  • DuoClustering2018 Preprocessed experimental and simulated scRNA-seq data sets used for evaluation of clustering methods for scRNA-seq data in Duò et al (2018). Also contains results from applying several clustering methods to each of the data sets, and functions for plotting method performance.

  • FlowSorted.Blood.EPIC Raw data objects to be used for blood cell proportion estimation in minfi and similar packages. The FlowSorted.Blood.EPIC object is based in samples assayed by Brock Christensen and colleagues; for details see Salas et al. 2018.

  • GIGSEAdata The gene set collection used for the GIGSEA package.

  • mcsurvdata This package stores two merged expressionSet objects that contain the gene expression profile and clinical information of -a- six breast cancer cohorts and -b- four colorectal cancer cohorts. Breast cancer data are employed in the vignette of the hrunbiased package for survival analysis of gene signatures.

  • MSMB Data sets for the book ‘Modern Statistics for Modern Biology’, S.P. Holmes and W. Huber

  • MTseekerData Provides examples for the MTseeker package vignette.

  • OMICsPCAdata Supporting data for package OMICsPCA

  • PepsNMRData This package contains all the datasets used in the PepsNMR package.

  • qPLEXdata qPLEX-RIME and Full proteome TMT mass spectrometry datasets.

  • RegParallel In many analyses, a large amount of variables have to be tested independently against the trait/endpoint of interest, and also adjusted for covariates and confounding factors at the same time. The major bottleneck in these is the amount of time that it takes to complete these analyses. With RegParallel, a large number of tests can be performed simultaneously. On a 12-core system, 144 variables can be tested simultaneously, with 1000s of variables processed in a matter of seconds via ‘nested’ parallel processing. Works for logistic regression, linear regression, conditional logistic regression, Cox proportional hazards and survival models, Bayesian logistic regression, and negative binomial regression.

  • RNASeqRData RNASeqRData is a helper experiment package for vignette demonstration purpose in RNASeqR software package.

  • sesameData Provides supporting annotation and test data for SeSAMe package.

  • TabulaMurisData Access to processed 10x (droplet) and SmartSeq2 (on FACS-sorted cells) single-cell RNA-seq data from the Tabula Muris consortium (

  • tcgaWGBSData.hg19 Data package for WGBS Data in TCGA. Data is stored as SummarizedExperiment Format. See vignette on how to extract the data and perform differential methylation analysis.

  • TENxPBMCData Single-cell RNA-seq data for on PBMC cells, generated by 10X Genomics.

New Workflows

There are 2 new workflow packages in this release of Bioconductor.

  • maEndToEnd In this article, we walk through an end-to-end Affymetrix microarray differential expression workflow using Bioconductor packages. This workflow is directly applicable to current “Gene” type arrays, e.g. the HuGene or MoGene arrays, but can easily be adapted to similar platforms. The data analyzed here is a typical clinical microarray data set that compares inflamed and non-inflamed colon tissue in two disease subtypes. For each disease, the differential gene expression between inflamed- and non-inflamed colon tissue was analyzed. We will start from the raw data CEL files, show how to import them into a Bioconductor ExpressionSet, perform quality control and normalization and finally differential gene expression (DE) analysis, followed by some enrichment analysis.

  • rnaseqDTU RNA-seq workflow for differential transcript usage (DTU) following Salmon quantification. This workflow uses Bioconductor packages tximport, DRIMSeq, and DEXSeq to perform a DTU analysis on simulated data. It also shows how to use stageR to perform two-stage testing of DTU, a statistical framework to screen at the gene level and then confirm which transcripts within the significant genes show evidence of DTU.

NEWS from new and existing Software Packages


Changes in version 1.11.7:


  • simplify functions ‘get_expression’ and ‘plot_expression’ (remove option to automatically use data from last aba_enrich-call)

  • ‘plot_expression’ now takes matrix from ‘get_expression’ as input, instead of calling ‘get_expression’ internally

  • add color key to ‘plot_expression’ heatmap when gene-associated variables are shown in a colored side bar

Changes in version 1.11.6:


  • sort output aba_enrich()[[1]] by FWER first and then by age category (previously it was sorted by age category first)

Changes in version 1.11.3:

  • remove all C++ code and depend on package GOfuncR instead

Changes in version 1.11.2:


  • when coordinates are used, remove genes with multiple gene-coordinates (coordinates are used when the familiy-wise error rate is corrected for gene length or spatial clustering of genes)

Changes in version 1.11.1:


  • allow for custom gene-coordinates (alternative to integrated coordinates; coordinates are used when the familiy-wise error rate is corrected for gene length or spatial clustering of genes)


Changes in version 0.99.0:

  • Submitted to Bioconductor


Changes in version 1.35.2 (2018-06-28):

  • Updating! Extend aFold to paired samples


Changes in version 0.99.8 (2018-09-06):

  • bugfix in squaremodelsummary: remove standard in singleplot call

Changes in version 0.99.6 (2018-07-26):

  • bugfix in linkvariants: no default freqindex

Changes in version 0.99.4 (2018-06-26):


  • changed linkmutationdata to linkvariants

  • linkvariants can estimate copies of heterozygous germline variants

  • linkvariants calculates the upper and lower bound of a given confidence level when read depth is given

  • changed postanalysisloop to accommodate linkvariants

  • added argument in runACE to specify genome build

  • several minor documentation amendments

  • improved coding robustness using seq and seq_along functions

Changes in version 0.99.0 (2018-05-24):


  • initial submission to Bioconductor


Changes in version 2.21.1 (2018-07-16):

  • Removed all mentions to old installer


Changes in version 1.53.2 (2018-10-22):


  • Link to Affx Fusion SDK archive on GitHub.

  • Spell corrections.

Changes in version 1.53.1 (2018-08-28):

  • Updated installation instructions in

Changes in version 1.53.0 (2018-04-30):

  • The version number was bumped for the Bioconductor devel version, which is now BioC 3.8 for R (>= 3.5.0).


Changes in version 1.5.2:


  • Rename GenenameFilter into GeneNameFilter and deprecate GenenameFilter (issue #22).


Changes in version 1.11.0:


  • Removed scripts for Pazar DB as website no longer active

  • Update from BiocInstaller to BiocManager


  • Species and taxonomyId are now validated against GenomeInfoDbData object


  • Fix TwoBit resource receipe. Converts DNA that is not A,C,T,G,N to N do to design of rtracklayer::export for TwoBit

  • Fix bug with assignment of tags in annotationhub

  • makeEpigenomeRoadMap recipe updated to account for XML bug that cannot handle http urls. updated to https


Changes in version 1.3.1:

  • fixed a bug where in anota2seqPlotPvalues and anota2seqPlotFC the contrast names were not displayed correctly when selecting only 1 contrast in case there were multiple

  • Using the anota2seqRun function with custom filtering parameters for maxP was still based on a maxPAdj of 0.15. This has been fixed, i.e. when maxP filtering is applied no maxPAdj filter will be used.


Changes in version 1.3.2:

  • Fix simple bug when no sample has only intercept coefficient.


Changes in version 3.11.2 (2018-09-04):


  • fitPrincipalCurve() now requires princurve (>= 2.1.2) and was updated to make use of new principcal_curve class instead of deprecated principcal.curve class. This update “should not” affect the results, but see for information of what has changed in the princurve package in this respect.

Changes in version 3.11.1 (2017-08-28):

  • Updated installation instructions in

Changes in version 3.11.0 (2017-04-30):

  • The version number was bumped for the Bioconductor devel version, which is now BioC 3.8 for R (>= 3.6.0).


Changes in version 0.99.25:

  • Update Vignette to just output html

Changes in version 0.99.02:

  • Add the Bioconductor webhook

Changes in version 0.99.01:

  • Submit the package to the Bioconductor project For Developers

  • All the functions name must have the prefix ‘artms’

  • Normalized all documentation using roxygen2 Deprecated

  • Nothing yet Defunct

  • Nothing yet


Changes in version 1.1.1:


  • need to specify number of cores to use a parallel environment

  • reference library (improvement of reference spectra by cleaning them)


Changes in version 1.17.2:

  • Bugfix ComBat.step2 by forcing ComBat input to be a matrix

  • Added new argument to assign.wrapper to specify direction of signature genes.

  • parameters file in assign.wrapper is now in yaml format.


Changes in version 1.33.2 (2018-06-29):

  • Fix NEWS

  • change maintainer email

Changes in version 1.33.1 (2018-05-15):

  • Fix NEWS


Changes in version 1.3.24 (2018-10-21):

  • Version bump to trigger new build

Changes in version 1.3.23 (2018-10-18):

  • Updated vignette to include simple SCE example without spike-in information

Changes in version 1.3.22 (2018-10-19):

  • Update of DESCRIPTION to require C++11

  • Once again, replacement of R::lgammafn by std::lgamma in c++ code

Changes in version 1.3.21 (2018-10-19):

  • Restores use of R::lgammafn due to errors in Bioconductor build report

Changes in version 1.3.20 (2018-10-18):

  • Minor updates to README and vignette (e.g. to include BASiCS sticker)

Changes in version 1.3.19 (2018-10-18):

  • Replacement of R::lgammafn by std::lgamma in c++ code (great speed-up! with thanks to Shian Su (@Shians))

Changes in version 1.3.18 (2018-10-15):

  • BASiCS_D_TestDE has been deprecated (replaced by BASiCS_TestDE)

  • SingleCellExperiment:: added to all calls of isSpike

  • Extra input check in BASiCS_MCMC to avoid issues due to multiple types of spike-ins being present in the data.

Changes in version 1.3.17 (2018-10-11):

  • New unit tests for different argument settings for the BASiCS_MCMC function

Changes in version 1.3.16 (2018-10-08):

  • Reduce checks for Data that was not generated with the newBASiCS_Data function

Changes in version 1.3.15 (2018-10-07):

  • Fixed bug when storing chains in the non-spikes case

Changes in version 1.3.13 (2018-09-30):

  • Some Rd files generated again

Changes in version 1.3.11 (2018-09-30):

  • Alan added as contributor

Changes in version 1.3.10 (2018-09-28):

  • Prevent BASiCS_Chain from crashing when StoreAdapt=TRUE for the regression case

  • Prevent plot function errors

  • Updated documentation using roxygen2

Changes in version 1.3.9 (2018-09-27):

  • Changed raw data accessor to ‘counts’ instead of ‘assay’

  • makeExampleBASiCS_Data now generates 30 cells instead of 20

  • Updated unit tests to match these 30 cells

Changes in version 1.3.8 (2018-09-05):

  • Updated (Travis/codecov badges) + updated citation to Cell Systems

Changes in version 1.3.7 (2018-09-05):

  • Commit to activate Travis/codecov

Changes in version 1.3.6 (2018-09-04):

  • Updated CITATION file

Changes in version 1.3.5 (2018-08-31):

  • Updated reference to latest paper

Changes in version 1.3.3 (2018-05-21):

  • Missing line added to test_data_examples.R

Changes in version 1.3.2 (2018-05-21):

  • Version bump only

Changes in version 1.3.1 (2018-05-21):

  • Unit tests created for selected C++ functions (Hidden_rDirichlet and Hidden_muUpdate)

  • Updated unit tests in spike-in parameter estimation to have tolerance (TEMPORARY FIX)

  • Minor updates in makeExampleBASiCS_Data and newBASiCS_Data function to allow different spike-in types (as in SingleCellExperiment)


Changes in version 0.99.19:

  • Replacing foreach with BiocParallel

  • Fix some errors in BB_fun

Changes in version 0.99.9:

  • Let more examples to be runnable; Updated vignette; Including SingleCellExperiment Class.

Changes in version 0.99.8:

  • Fix some errors.

Changes in version 0.99.4:

  • Apply corrections proposed by the reviewer, for more details please see <URL:>

Changes in version 0.99.1:

  • Fix two warnings reported by Bioconductor * WARNING: Use TRUE/FALSE instead of T/F, Found in files: tests/testthat/test-bayNorm.r * WARNING: Use is() or !is()

Changes in version 0.99.0:

  • Pass all checks of both R CMD build and R CMD BiocCheck.

  • Future work: * Vignette needs to be further improved. * Need to Improve man pages. * Submit to Bioconductor.


Changes in version 1.3.3:

  • update format for NEWS

Changes in version 1.3.2:

  • update citation and fix bugs

Changes in version 1.3.1:

  • update citations


Changes in version 1.4.0:

  • Removed native support for RleMatrix and packed symmetric matrices.

  • Added multi-row/column getters.

  • Added mechanism for native support of arbitrary developer-defined matrices.

  • Switched to row/colGrid() for defining chunks in unsupported matrices.


Changes in version 1.13.11 (2018-10-25):

  • implementation of further tests

Changes in version 1.13.10 (2018-10-24):

  • test for the gdepoch function

  • simplification of code

  • performance improvements

Changes in version 1.13.9 (2018-10-23):

  • test for the loss function

  • some simplifications

Changes in version 1.13.8 (2018-10-22):

  • first implementation of tests with testthat

  • simplifications of the code

Changes in version 1.13.7 (2018-10-10):

  • small bugfix

Changes in version 1.13.6 (2018-10-05):

  • some minor issues with the calculation of p-values are fixed

Changes in version 1.13.5 (2018-10-04):

  • checks for the validity of inputs added

  • some performance improvements

Changes in version 1.13.4 (2018-10-02):

  • major performance improvement

Changes in version 1.13.3 (2018-09-28):

  • usage of data.table for various functions for performance improvement

  • simplification of the source code

Changes in version 1.13.2 (2018-09-27):

  • bug fixed that, where p-values couldn’t be calculated for a gene with only missing values in a batch (#1)

Changes in version 1.13.1 (2018-09-25):

  • BEclear uses now BiocParallel instead of snowfall for parallelisation

  • roxygen2 is now used for the generating the documentation

  • major code refactoring

  • some minor bug fixes

  • performance improvements


Changes in version 2.6.2:

  • Fix issue in the formatData() function. It is now possible to format using fpkm expression values when using Bgee 14.0.

  • Implementation of regression tests

  • Update vignette and README

Changes in version 2.6.1:

  • Fix issue on Bgee 14.0 tar.gz annotation file management.

  • Update README and DESCRIPTION files.


Changes in version 1.1.5 (2018-07-02):

  • Fixed R documentation notes # Updated date field in DESCRIPTION


Changes in version 1.9.07:

  • replace DOSE::dotplot by clusterProfiler::dotplot

  • replace r_data by r_info in reports

  • not need to define genelist in r_data

  • update ReactomeFI.RDS file (version 2017)

  • update DisGeNet0918.RDS file (version September 2018), move it from to github/kmezhoud

Changes in version 1.9.06:

  • rm warning message for min and max functions

  • run getFreqMutData() when getListProfData() instead getCoffeeWheel_Mut(). Avoid error when loading x profiles data to workspace.

  • include Tools panel into Workspace panel.

  • update Overview image

Changes in version 1.9.05:

  • r_data vs r_info …

  • use r_info for dataset list and r_data for genes list

  • set progress bar

Changes in version 1.9.04:

  • add style.css file: raduce padding-top to 0px

Changes in version 1.9.03:

  • modify stop function

  • update paste gene list function

Changes in version 1.9.02:

  • upload and download using Rstudio file browser remove plot_downloader function and replace it by download_link (defined in radiant.R file)

  • add radiant_old.R file for needed functions but not longer used by

Changes in version 1.9.01:

  • replace getdata() by get_data()

  • replace factorizer() by lapply(.,factor)


Changes in version 1.17:


  • (1.17.21) Added quit-with-status option to both BiocCheck and BiocCheckGitClone for compatibility with travis

  • (1.17.18) Update devel to use BiocManager instructions instead of BiocInstaller

  • (1.17.17) Add a new function that can be run interactive or command line BiocCheckGitClone which is only run on a source directory not a tarball. This will check for bad system files

  • (1.17.17) BiocCheck addition: Checks vignette directory for intermediate and end files that should not be included.

  • (1.17.16) Checks for Bioconductor package size requirement if checking tarball


  • (1.17.19) Updated internal functions to use BiocManger instead of BiocInstaller


Changes in version 1.5:


  • (v. 1.5.1) Add ‘exact = ‘ for exact matching in bfcquery(), bfcrpath(). (v. 1.5.2) defaults to TRUE for bfcrpath()


  • (v. 1.5.2) bfcrpath() more robust when adding regular expression rnames.


  • (v. 1.5.4) bfcpath() implementation change. Only displays rpath and can work with multiple rids. bfcpath only for rpath access while bfcrpath is the option to get or add.


Changes in version 1.31.2:


  • ‘BiocInstaller’ is currently deprecated. All installation of Bioconductor packages will be done via BiocManager a CRAN package.


  • The documentation incorrectly refered to remotes::install which is not an exported function of the package. This link was fixed.


Changes in version 1.0.0:

  • New package kmknn, for k-means-based k-nearest neighbor detection.


Changes in version 1.5.4:

  • Improved spelling

  • Reduced the complexity fo combineScoresPar and combineScores.

  • Improve efficiency of code in vignettes.

  • Change the news section

  • Adding a section about GeneOverlap package.

  • Changed the License


Changes in version 1.16:


  • (v 1.15.9) BatchtoolsParam() gains resources=list() for template file substitution.

  • (v 1.15.12) bpexportglobals() for all BPPARAM exports global options (i.e., base::options()) to workers. Default TRUE.


  • (v 1.15.6) bpiterate,serial-method does not return a list() when REDUCE present (

  • (v 1.15.7) bpaggregate,formula-method failed to find BPREDO (

  • (v 1.15.13) bplappy,BatchtoolsParam() coerces List to list (

  • (v 1.15.14) implicit loading of BiocParallel when loading a third- party package failed because reference class initialize() methods are not installed correctly. This bug fix results in signficant revision in the implementation, so that valid objects must be constructed through the public constructors, e.g., BatchtoolsParam()


Changes in version 0.99.0:

  • This package implements various functions to find template strand changepoints in Strand-seq data.


Changes in version 1.17:

  • BSseq() will no longer reorder inputs. Previously, the returned BSseq object was ordered by ordering the loci, although this behaviour was not documented. BSseq() may still filter out loci if rmZeroCov = FALSE or collapse loci if strandCollapse = FALSE or duplicate loci are detected, but the relative order of loci in the output will match that of the input.

  • Fix bug with maxGap argument of BSmooth(). The bug meant that the ‘maximum gap between two methylation loci’ was incorrectly set to 2 * maxGap + 1 instead of maxGap. This likely did not affect results for users who left the default value of maxGap = 10^8 but may have affected results for small values of maxGap.


Changes in version 0.99.13 (2018-10-09):

  • Improved the ``postprob_DE_thr_fun’’ function.

Changes in version 0.99.6 (2018-07-27):

  • Created a NEWS.Rd file parsable by utils::news within the inst folder


Changes in version 1.5:

  • Added new functions for spatial analysis of clusters: findLinks finds nearby pairs of clusters (for example TSSs and enhancers) and calculates the correlation of expression between them. findStretches find stretches along the genome where clusters are within a certain distance of eachother (for example groups of enhancer forming a super enhancer) and calculates the average pairwise correlation between members.

  • Changed the way clustering works: CAGEfightR uses coverage() to calculate genome-wide signals and now rounds the resulting signal to a certain number of digits (this can be modified via the CAGEfightR.round option), to prevent small positive or negative values due to floating point errors. This makes clustering more stable meaning the tuneTagClustering function is now deprecated. This should also increase the speed of most functions.

  • CAGEfightR now uses GPos instead of GRanges for storing CTSSs, this should result in improved memory performance.

  • Several changes to clusterBidirectionality: Balance is now calculated using the midpoint as well (preventing some rare cases where the midpoint could mask a single highly expressed CTSS), the pooled CTSS signal is now prefiltered for bidirectionality to increase speed and custom balance function can be provided (Bhattacharyya coefficient and Andersson’s D are included).

  • Added new check-functions to make it easier to check if objects are formatted correctly


Changes in version 1.24.0:


  • plotAnnot(): the “group” argument now accepts formulas such as “~ a + b” to indicate names of metadata column that will be pasted together to form a new group factor.


  • Prevent mergeSamples() from producing colData that cause other functions to crash later when coercing to data.frame.

  • Repaired paraclu support for CAGEset objects.

  • normalizeTagCount() works again on CAGEset objects.

  • consensusClustersGR() reports expression score of the selected sample (instead of silently ignoring the “sample” argument and reporting expression sum on all the samples).


Changes in version 1.99.2 (2018-10-28):


  • Updated vignettes for Cardinal 2.0


  • Removed a unit test broken on Windows

Changes in version 1.99.1 (2018-10-26):


  • Added vignettes and documentation for Cardinal 2.0

Changes in version 1.99.0 (2018-10-25):


  • Version bump for Cardinal v2 release candidate

Changes in version 1.13.3 (2018-10-24):


  • Added ‘process’ method for queueing delayed processing functions to an imaging dataset and applying them

  • Added new processing methods for Cardinal v2 including new versions of ‘normalize’, ‘smoothSignal’, ‘reduceBaseline’, ‘peakPick’, ‘peakAlign’, and ‘peakFilter’

  • Added new ‘peakBin’ function for binning peaks

  • Updated ‘show’ method for new Cardinal v2 classes

  • New support for exporting ‘processed’ imzML files via the ‘writeImzML’ function

Changes in version 1.13.2:


  • Added new classes for Cardinal v2 including ‘XDataFrame’, ‘PositionDataFrame’, ‘MassDataFrame’, ‘ImagingExperiment’, ‘SparseImagingExperiment’, and ‘MSImagingExperiment’

Changes in version 1.13.1:


  • Updated installation instructions for “CardinalWorkflows”

Changes in version 1.12.1:


  • Fixed bug in reading Analyze 7.5 files


Changes in version 1.4.0 (2018-10-30):

New Features

  • obtainOneStudy() and obtainMultipleStudies() functions can obtain data for groups of genes each possess more than 250 genes (Virtually unlimited gene number).

  • A new argument for xlsxOutput() function to exchange the columns and rows.


Changes in version 1.1.2:


  • Added C++ code update step in vb_factorize(…, useC=TRUE)

  • Added Singular value decomposition initializer for vb_factorize(…, initializer=’svd2’) random initial condition: initializer=’random’

  • Changed default: filter_genes(…,rescue.genes=FALSE)

  • Changed filter_genes(), vmr.min action from vmr >= vmr.min to vmr > vmr.min (removes genes with vmr=0)

  • Added parallel run for vb_factorize(…, ncores=10)

  • Added feature_map(…)


Changes in version 0.99.1:


  • Code style.

  • Do not attempt to multithread on windows (suggest mulithread on linux).

Changes in version 0.99.0:


  • Initial Version.


Changes in version 0.99.15:

  • Bugfixes: - Adjusted NAMESPACE for most recent ‘SingleCellExperiment’ release

Changes in version 0.99.14:

  • Bugfixes: - Filtering. Captures invalid user input. - Clustering. Parameter settings resulting in a minimum number of samples per initial state <= 1 are captured.

Changes in version 0.99.13:

  • Bugfixes: - Visualization. Package is compatible with most recent ‘ggplot2’ release (3.x.x).

  • Updated CITATION

Changes in version 0.99.0:

  • Public pre-release for Bioconductor submission

  • CellTrails is fully compatible with a ‘SingleCellExperiment’ object

  • Bugfixes


Changes in version 1.7.1:


  • Introduced support for oncofuse. Ref and


Changes in version 3.15.2:

  • fix the bug in binOverRegions and binOverGene

Changes in version 3.15.1:

  • Fix the bug in assignChromosomeRegion for the Jaccard index calculation.


Changes in version 1.7.2:


  • Compatibility fixes for the new release of ggplot2 (3.0.0).

  • seqlevels() that are smaller than binsize are dropped properly in fixedWidthBins() and variableWidthBins().


Changes in version 1.9.2:

  • Reformatted NEWS file.

Changes in version 1.9.1:

  • Reconfigured KEGG pathway downloading via KEGG API.


Changes in version 2.2.0:

  • getClasses is no longer a slot of PredictParams. Every predictor function needs to return either a factor vector of classes, a numeric vector of class scores for the second class, or a data frame with a column for the predicted classes and another for the second-class scores.

  • Cross-validations which use folds ensure that samples belonging to each class are in approximately the same proportions as they are for the entire data set.

  • Classification can reuse fitted model from previous classification by using previousTrained function.

  • Feature selection using gene sets and networks. Classification can use meta-features derived from the individual features used for feature selection.

  • tTestSelection function for feature selection based on ordinary t-test statistic ranking. Now the default feature selection function, if none is specified.

  • Tuning parameter optimisation metric is specified by providing a tuneOptimise parameter to TrainParams rather than depending on ResubstituteParams being used during feature selection.


Changes in version 2.1.5 (2018-06-28):


  • Add functionality to getBestFeatures to allow edgeR for DE, as well as weights used with edgeR for zinbwave compatability. As part of this change: - Removed isCount argument and replaced with more fine-grained DEMethod argument in getBestFeatures, mergeClusters; or mergeDEMethod in RSEC. - Change to class definition: added slot merge_demethod to keep track of the DE method used in merging

  • Change function names (old function name is now depricated): - combineMany -> makeConsensus - removeUnclustered -> removeUnassigned

  • Arguments to functions changed: - combineProportion -> consensusProportion in RSEC - combineMinSize -> consensusMinSize in RSEC - sampleData -> colData to match SummarizedExperiment syntax (in many plotting functions). - alignSampleData -> alignColData in plotHeatmap - ignoreUnassignedVar -> filterIgnoresUnassigned in mergeClusters (and other functions) for clarity. - removeNegative -> removeUnassigned in getBestFeatures for uniformity - Removed largeDataset option to subsampleClustering because no longer provides advantage. - nBlank -> nBlankFeatures in makeBlankData to allow for samples

  • Created functions: - primaryClusterLabel and primaryClusterType - getReducedData - assignUnassigned: assigns unassigned samples to nearest cluster - renameClusters and recolorClusters: assign new names/colors to clusters within a particular clustering - clusterMatrixColors: wrapper to convertClusterLegend to return matrix like clusterMatrix only with colors in place of the internal cluster ids (like existing clusterMatrixNamed) - plotClustersTable for plotting a heatmap showing the results of tableClusters - subsetByCluster for subsetting CE object to only those samples in a particular cluster(s) of a clustering. - plotFeatureScatter for a scatter plot of 2+ features (genes) colored by cluster - addToColData and colDataClusters adding clustering information to colData of object. addToColData returns object with colData augmented, while colDataClusters just returns the DataFrame with clusterings added. - updateObject to update historical object created from previous versions to the current class definitions.

  • Added arguments: - whichAssay to all functions to allow the user to select the assay on which the operations will be performed. - stopOnErrors to RSEC - nColLegend to plotReducedDims - subsample and sequential to RSEC to allow for opting out of those options (but default is TRUE unlike clusterMany) - nBlankSamples and groupsOfSamples to makeBlankData to allow for separating samples (columns) - add and location to plotClusterLegend

  • makeBlankData will now allow for making blank columns to separate groups of samples.

  • plotDendrogram now allows for plotting of colData (previously sampleData) like plotHeatmap or plotClusters

  • clusterMany now allows user-defined ClusterFunction objects to argument clusterFunction.

  • Removed restriction in plotClustersWorkflow that only clusterType="clusterMany" allowed.

  • Allow getClusterManyParams to search old clusterMany runs as well.

  • Added table method to plotHeatmap (for plotting heatmap of results of table function)

  • Added error catch if try to give argument whichCluster to mergeCluster.

  • Added error catch if give param whichClusters to functions that only take whichCluster (singular) as an argument

  • plotFeatureBoxplot now returns (invisibly) the colors and clusterIds along with the boxplot information.


  • Add check for merge_nodeMerge table that mergeClusterId column can’t be NA for entries where isMerged=TRUE

  • Fix internal .makeIntegerClusters so that if given values 1:K for input clustering will retain these same values (Issue #227)

  • mergeClusters now returned object saves the merge information (and deletes old info and updates clusterType/clusterLabel of existing merge clusters), even if mergeMethod="none".

  • Fix removeClusterings so doesn’t loose merge info unless deleting relevant clusterings.

Changes in version 2.1.4 (2018-06-27):


  • Fix tests that fail in devel version of Bioconductor (due to changes in other packages)

Changes in version 2.1.3 (2018-05-24):


  • Fix bug in how clusterMany and defaultNDims dealt with filtering choices in reduceMethod.

  • Fixed bug in how clusterMany assigned label names

  • Fixed bug so that clusterMany labels are increased (iteration version added) if clusterMany is rerun. Also, user-defined labels for functions like mergeClusters are now updated with iteration value if they are duplicated.

Changes in version 2.1.2 (2018-05-17):


  • Fix so that estimates of the proportion non-null in mergeClusters are always positive.

  • Fix so that calculation of filter with ignoreUnassignedVar doesn’t delete existing base filter of same type.

  • Fix plotClustersWorkflow where wrong cluster was grabbed to plot.

  • Fix bug in plotDendrogram where colors of clusters plotted with could be subsumbed by color of previous clustering. (git Issue #220)

Changes in version 2.1.1 (2018-05-15):


  • Fixed error introduced in 2.0.0 where arguments to mergeCutoff and mergeLogFCcutoff were passed instead to dendroNDims.


Changes in version 1.15.1 (2018-05-30):

  • add dotplot in heatmapPEI and vignettes

  • multi-group labelling


Changes in version 1.19.4:

  • Fixed a bug in the FunctionalityScore and PolyfunctionalityScore APIs when markers= argument is passed in and not null.


Changes in version 1.17.1:

  • Removed support for SAMseq since samr has been removed from CRAN


Changes in version 1.15.1:

  • The following function is updated + heatmapPlot.R: the function was updated removing a useless call to hclust, thus reducing by half the time required for clustering. + topGOres.R: the function was sligtly modified to be more efficient in case of GO enrichment analysis of multiple gene sets. The indexing of the ontology is now performed only once, greatly improving the speed of the function.


Changes in version 1.19.1:

  • Heatmap(): no column name added if the input matrix is a one-column matrix.

  • oncoPrint(): scales the the row annotations are now the same if rows are split.


Changes in version 0.99.0:

  • Original submission to Bioconductor


Changes in version 0.99.11:

  • New package coRdon, for analysis of codon usage.


Changes in version 0.99.0:

  • To comply with Bioconductor guidelines, the random seed (for subsampling of samples and features for dispersion and correlation calculations) is no longer set inside the functions, and the argument is removed from countsimQCReport(). For reproducible results, please set the random seed explicitly in the R session.

Changes in version 0.5.2:

  • Add options to silence progress indicators

  • Fixes in dispersion visualization

Changes in version 0.5.0:

  • Add a number of quantitative evaluation criteria and tests for pairwise comparison of data sets

  • The argument subsampleSize to the countsimQCReport() function now determines the number of observations for which (time-consuming) statistics are calculated

  • A new argument maxNForCorr is added to the countsimQCReport() function to indicate the number of observations for which pairwise correlations are calculated

  • Improvements in documentation

Changes in version 0.4.6:

  • Allow code folding when showCode = TRUE

Changes in version 0.4.5:

  • Allow data frames or matrices as input (assuming design = ~ 1)

  • First implementation of area between ECDFs

  • Increase transparency of points in scatter plots

Changes in version 0.4.4:

  • Included effective library size evaluation.

Changes in version 0.4.2:

  • Allowed using just a subset of the samples for dispersion calculations.

Changes in version 0.4.1:

  • Added pairwise sample and variable correlation distributions.

  • Added box plots and violin plots.

Changes in version 0.4.0:

  • Major overhaul of function and argument names for increased consistency.

Changes in version 0.3.2:

  • Added mean-variance plots.

Changes in version 0.3.0:

  • Added K-S statistics.

  • Added line density plots.


Changes in version 1.9.2:

  • Keep metadata columns in targets

  • Adds function for splitting insertion sequences


Changes in version 1.16.0:

  • Added normFactors() function to avoid confusion when normOffsets() returns factors.

  • Deprecated type=”scaling” option in normOffsets().

  • Added calculateCPM() function for convenient calculation of (log-)CPMs.

  • Split up consolidateSizes() function into consolidateWindows(), consolidateTests() and consolidateOverlaps(). Deprecated consolidateSizes() itself.

  • Switched output of combineTests() and getBestTest() and related functions to a DataFrame.

  • Modified mergeWindows() behaviour with specified sign=, for dealing with nested windows of opposing sign.

  • Altered controlClusterFDR() to take the largest adjusted p-value threshold that yields a cluster-level FDR below target=.

  • Simplified detailRanges() output so that it no longer returns an arbitrary exon number.


Changes in version 1.20.3:


  • Fix bug in function PrepareAnnotationRefseq.R

  • Update function aaVariation.R to avoid translate ‘TTG’ and ‘CTG’ into ‘M’


Changes in version 1.6.0:

  • Restructured the CyData class for simplicity and internal fields.

  • Deprecated plotCell* functions, renamed them to plotSphere*.

  • Added the createColorBar() convenience function.

  • Removed the diffIntDist() function.

  • Restored option for quantile normalization in normalizeBatch(). Switched to deterministic algorithm for sampling when mode=”warp”.


Changes in version 3.6:

  • Contains all modifications and fixes from 1.8.2 to 1.9.5


Changes in version 1.9.2:


  • PacBio CCS reads up to 3 kilobases are now supported. See also PacBioErrfun, the new and recommended error-estimation function for PacBio CCS data.


  • primer.fwd has been replaced by orient.fwd in the filterAndTrim function. This option consistently orients mixed-orientation single-end or paired-end reads based on matching the provided sequence fragment to the start or end of each read (or paired read). Intended for use with mixed-orientation reads that included sequenced primers. If primers aren’t included in the amplicons, an external re-orientation solution remains preferable.

  • trimRight has been added to the filterAndTrim function. This removes the specified number of bases from the end (“right” side) of each read.


  • collapseNoMismatch now collapses identical sequences as well (previous behavior is togglable).

Changes in version 1.9.1:


  • mergePairs now gracefully handles cases when zero reads succesfully merge.

  • plotQualityProfile now works correclty when given a directory containing fastq files.


Changes in version 1.5.2:

  • The DaMiR.normalization function embeds also the ‘logcpm’ normalization.

  • Now, DaMiR.EnsembleLearning calculates also the Positive Predicted Values (PPV) and the Negative Predicted Values (NPV).

  • Three new functions have been implemented for the binary classification task: DaMiR.EnsembleLearning2cl_Training, DaMiR.EnsembleLearning2cl_Test and DaMiR.EnsembleLearning2cl_Predict. The first one allows the user to implement the training task and to select the model with the highest accuracy or the average accuracy; the second function allows the user to test the selected classification model on a test set defined by the user; the last function allows the user to predict the class of new samples.

  • Removed black dots in the violin plots.

Changes in version 1.4.1:

  • Adjusted Sensitivity and Specificity calculations.


Changes in version 1.11.1:

  • fixed unit test for plotting without replicates as DESeq2 no longer supports silentl treating as replicates since version 1.22


Changes in version 1.9.21:

  • Last publication fixes

Changes in version 1.8.6:

  • The columns that have strings removed while loading

  • Labels can be changed in the main plots

  • Plot Information box added to give more information about the plots.

Changes in version 1.8.4:

  • Calculated padj and foldchange columns added to all detected genes result

  • Normalization issue is fixed in comparison table

Changes in version 1.8.3:

  • EdgeR and Limma

Changes in version 1.8.2:

  • Package installation changed to warning

  • Dependancies removed from DESCRIPTION to suppress loading messages

  • Biarxiv citation added

Changes in version 1.8.1:

  • Interactive heatmap height and width fix

  • DEBrowser turned to a modular structure. The modules can be used in other shiny applications.

  • More interactivity added to Heatmaps and main plots.

  • Lasso selection is added to main plots


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 1.17.8:

  • Fix: typo in as.DEGSet from DESeq2 object.

Changes in version 1.17.7:

  • Fix: re-format NEWS file

Changes in version 1.17.6:

  • Fix: Error in degCovariate when no correlation exists.

Changes in version 1.17.5:

  • Fix: Fix documentation warning.

Changes in version 1.17.4:

  • Feature: Reduce parameter is used to remove outlier points after clustering genes.

  • Feature: Add maximum log2FoldChange to the significance output when multiple comparisons are used as inputs.

  • Feature: Remove non-mapped genes in degPlot.

  • Feature: Add specific function to plot degPatterns clusters.

  • Fix: Support DESeqResults for list of DEGSets.

  • Feature: Add variable selection for covariates that correlate with PCs in degCovariate function.

  • Feature: Add lasso as an option to variable selection in covariate analysis.

  • Feature: Fill with colors only significant variables by lm or lasso, and draw borber for correlated variables by cor.test.

Changes in version 1.17.3:

  • Fix: degCovariates works with metadata only with numerical variables

    • Feature: Improve support for DEGSet conversion.
  • Fix: Remove theme set up for degPCA plot.

  • Feature: Make function to generate colors for metadata variables for annotation column in heatmap figure.

  • Feature: Improve degCovariates to add effect size of the covariates. Thanks to @vbarrera

  • Fix: Improve degCovariates man pages.

Changes in version 1.17.1:

  • Fix: remove discrete scale color in degPCA.

  • Feature: Return same output for degPatterns with single genes. Thanks Amir Jassim.

  • Feature: Allow custom y-axis lab in degPlot. Thanks @vbarrera.


Changes in version 1.34.1:

  • remove function samWrapper


Changes in version 0.8.0:


  • Add get/setAutoBlockSize(), getAutoBlockLength(), get/setAutoBlockShape() and get/setAutoGridMaker().

  • Add rowGrid() and colGrid(), in addition to blockGrid().

  • Add get/setAutoBPPARAM() to control the automatic ‘BPPARAM’ used by blockApply().

  • Reduce memory usage when realizing a sparse DelayedArray to disk

    + On-disk realization of a DelayedArray object that is reported to be sparse
    (by is_sparse()) to a "sparsity-optimized" backend (i.e. to a backend with
    a memory efficient write_sparse_block() like the TENxMatrix backend imple-
    mented in the HDF5Array package) now preserves sparse representation of
    the data all the way. More precisely, each block of data is now kept in
    a sparse form during the 3 steps that it goes thru: read from seed,
    realize in memory, and write to disk.
  • showtree() now displays whether a tree node or leaf is considered sparse or not.

  • Enhance “aperm” method and dim() setter for DelayedArray objects. In addition to allowing dropping “ineffective dimensions” (i.e. dimensions equal to 1) from a DelayedArray object, aperm() and the dim() setter now allow adding “ineffective dimensions” to it.

  • Enhance subassignment to a DelayedArray object.

    + So far subassignment to a DelayedArray object only supported the **linear
    form** (i.e. x[i] <- value) with strong restrictions (the subscript 'i'
    must be a logical DelayedArray of the same dimensions as 'x', and 'value'
    must be an ordinary vector of length 1).
    + In addition to this linear form, subassignment to a DelayedArray object
    now supports the **multi-dimensional form** (e.g. x[3:1, , 6] <- 0). In
    this form, one subscript per dimension is supplied, and each subscript
    can be missing or be anything that multi-dimensional subassignment to
    an ordinary array supports. The replacement value (a.k.a. the right
    value) can be an array-like object (e.g. ordinary array, dgCMatrix object,
    DelayedArray object, etc...) or an ordinary vector of length 1. Like the
    linear form, the multi-dimensional form is also implemented as a delayed
  • Re-implement internal helper simple_abind() in C and support long arrays. simple_abind() is the workhorse behind realization of arbind() and acbind() operations on DelayedArray objects.

  • Add “table” and (restricted) “unique” methods for DelayedArray objects, both block-processed.

  • range() (block-processed) now supports the ‘finite’ argument on a DelayedArray object.

  • %*% (block-processed) now works between a DelayedMatrix object and an ordinary vector.

  • Improve support for DelayedArray of type “list”.

  • Add TENxMatrix to list of supported realization backends.

  • Add backend-agnostic RealizationSink() constructor.

  • Add linearInd() utility for turning array indices into linear indices. Note that linearInd() performs the reverse transformation of base::arrayInd().

  • Add low-level utilities mapToGrid() and mapToRef() for mapping reference array positions to grid positions and vice-versa.

  • Add downsample() for reducing the “resolution” of an ArrayGrid object.

  • Add maxlength() generic and methods for ArrayGrid objects.


  • Multi-dimensional subsetting is no more delayed when drop=TRUE and the result has only one dimension. In this case the result now is returned as an ordinary vector (atomic or list). This is the only case of multi-dimensional single bracket subsetting that is not delayed.

  • Rename defaultGrid() -> blockGrid(). The ‘max.block.length’ argument is replaced with the ‘block.length’ argument. 2 new arguments are added: ‘chunk.grid’ and ‘block.shape’.

  • Major improvements to the block processing mechanism. All block-processed operations (except realization by block) now support blocks of arbitrary geometry instead of column-oriented blocks only. ‘blockGrid(x)’, which is called by the block-processed operations to get the grid of blocks to use on ‘x’, has the following new features: + It’s “chunk aware”. This means that, when the chunk grid is known (i.e. when ‘chunkGrid(x)’ is not NULL), ‘blockGrid(x)’ defines blocks that are “compatible” with the chunks i.e. that any chunk is fully contained in a block. In other words, blocks are chosen so that chunks don’t cross their boundaries. + When the chunk grid is unknown (i.e. when ‘chunkGrid(x)’ is NULL), blocks are “isotropic”, that is, they’re as close as possible to an hypercube instead of being “column-oriented” (column-oriented blocks, also known as “linear blocks”, are elongated along the 1st dimension, then along the 2nd dimension, etc…) + The returned grid has the lowest “resolution” compatible with ‘getAutoBlockSize()’, that is, the blocks are made as big as possible as long as their size in memory doesn’t exceed ‘getAutoBlockSize()’. Note that this is not a new feature. What is new though is that an exception now is made when the chunk grid is known and some chunks are >= ‘getAutoBlockSize()’, in which case ‘blockGrid(x)’ returns a grid that is the same as the chunk grid. + These new features are supposed to make the returned grid “optimal” for block processing. (Some benchmarks still need to be done to confirm/quantify this.)

  • The automatic block size now is set to 100 Mb (instead of 4.5 Mb previously) at package startup. Use setAutoBlockSize() to change the automatic block size.

  • No more ‘BPREDO’ argument to blockApply().

  • Replace block_APPLY_and_COMBINE() with blockReduce().


  • No-op operations on a DelayedArray derivative really act like no-ops. Operating on a DelayedArray derivative (e.g. RleArray, HDF5Array or GDSArray) will now return an objet of the original class if the result is “pristine” (i.e. if it doesn’t carry delayed operations) instead of degrading the object to a DelayedArray instance. This applies for example to ‘t(t(x))’ or ‘dimnames(x) <- dimnames(x)’ etc…


Changes in version 1.15.4:


  • Switched from ‘outfile’ to ‘log’ when invoking BiocParalle::SnowParam(). Thus define_cluster() now has a mc.log argument instead of mc.outfile.

Changes in version 1.15.2:


  • Fix a message regarding the deprecated IRanges subset method.

Changes in version 1.15.1:


  • Use BiocManager


Changes in version 1.15.1:


  • Use BiocManager


Changes in version 1.15.1:


  • Use BiocManager


Changes in version 1.22.0:

  • No replicate designs no longer supported (previous version began deprecation with a warning).

  • unmix() now optionally will return the correlation (in the variance stabilized space) of the fitted data to the original data, and the matrix of fitted data (format=”list”). Argument ‘loss’ was changed to ‘power’. Will give warning if the columns of ‘pure’ have high correlation (in the variance stabilized space).

Changes in version 1.21.21:

  • Improved code for ‘linearModelMu’ (an internal fitting function used in dispersion estimation for some models) contributed by Wolfgang Huber speeds up an internal step by 2 orders of magnitude.

Changes in version 1.21.15:

  • Rows of the weights matrix which would produce a degenerate design matrix, instead of giving an error, will produce a warning, and these rows will be treated as if they contained all zeros (mcols(dds)$allZero and mcols(dds)$weightsFail will be set to TRUE).

Changes in version 1.21.14:

  • The nbinom{WaldTest,LRT} functions will not stop if the design produces a model matrix that is not full rank and betaPrior=FALSE (default). This was assumed by the DESeq2 code, because errors are produced at object construction and at dispersion estimation, but it was possible to call nbinomLRT() from DEXSeq after dispersion estimation and end up with a full model matrix that was not full rank. Instead testForDEU() should be called from DEXSeq.

Changes in version 1.21.13:

  • Adding back a feature from version 1.15, where contrasts of two groups where both had all zero counts would have the LFC zero-ed out, rather than output a small but non-zero value. It’s preferable for the Wald test that the LFC be set to zero for such contrasts.

Changes in version 1.21.9:

  • DESeq() now only says one time ‘using supplied model matrix’, previously this was repeated three times from sub-functions. Sub-functions therefore no longer print this message.

  • Fixed bug when lfcShrink run directly after LRT with supplied model matrices.

  • Added heuristic to prevent Cook’s outlier based filtering when the max Cook’s sample has lower counts than 3 other samples. Restricted to two group comparison datasets.


Changes in version 1.0.5:

  • Optimization of speed and memory.

Changes in version 1.0.1:

  • Optimization of memory management.


Changes in version 1.7.4:

  • Reformatted NEWS file.

Changes in version 1.7.3:

  • Updated rankedList argument in DEsubs() to receive gene identifiers in any of the supported mRNAnomenclatures.

Changes in version 1.7.2:

  • Removed ‘Significance Analysis of Microarrays’ (SAM) from available differential expression analysis options due to the removal of its package from the ecosystem.


Changes in version 1.14.0:

  • Added the readMTX2IntSet() function to create InteractionSets from file.


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)


Changes in version 1.7.3:

  • Added citation


Changes in version 1.3.1:


  • A new citation is added.

  • Several bugs are corrected.


Changes in version 1.1.20 (2018-10-11):

  • Minor bug fix for a rare situation that occured in the case of a multi-level covariate of interest if the region level model fitting procedure did not converge.

Changes in version 1.1.2 (2018-05-09):

  • The newly added chrsPerChunk argument specifies the number of chromosomes to compute at a time (default is 1).


Changes in version 1.1.2:


  • add missing space to vignette

Changes in version 1.1.1:


  • move from bioclite to BiocManager

Changes in version 1.1.0:


  • DominoEffect in BioC 3.8 development release


Changes in version 1.1.1:


  • New function called draw_folding(). This function allows the drawing of the STRAND, HELIX and TURN types which denote regions of the proteins that assemble as beta-strands, alpha helicies or make a turn in the 3D structure of the protein.

  • New function called parse_gff(). This function imports files or urls that link to a GFF3 format and parses the data to allow it to be plotted.


Changes in version 1.2.0:

  • Added removeSwappedDrops() for removing swapping in other types of droplet-based data.

  • Added alpha= argument to testEmptyDrops() to support overdispersion during sampling. Returned arguments and estimates in metadata of testEmptyDrops(), emptyDrops().

  • Added encodeSequences() for convenient 2-bit encoding of sequences.

  • Added get10xMolInfoStats() function to compute per-cell statistics from a molecule info file.

  • Deprecated read10xMatrix(), as it does not add much practical value over Matrix::readMM().

  • Support the 10X sparse HDF5 format in read10xCounts().

  • Support the 10X sparse HDF5 format in write10xCounts().


Changes in version 1.11.1:

  • Added support to count on different feature types rather than exons (thanks to John Chuang)


Changes in version 3.24.0:

  • New functions catchKallisto() and catchSalmon() to read outputs from kallisto and Salmon and to compute overdispersion factors for each transcript from bootstrap samples.

  • New function readBismark2DGE() to read coverage files created by Bismark for BS-seq methylation data.

  • New method “TMMwzp” for calcNormFactors() to better handle samples with a large proportion of zero counts.

  • The default value for prior.count increased from 0.25 to 2 in cpm() and rpkm(). The new value is more generally useful and agrees with the default values in aveLogCPM() and with the DGEList method for plotMDS().

  • zscoreNBinom() now supports non-integer q values.

  • The scaleOffset() S3 methods for DGEList and default objects are now registered in the NAMESPACE. Previously the functions were exported but not registered as S3 methods.

  • The rowsum() method for DGEList objects (rowsum.DGEList) now automatically removes gene annotation columns that are not group-level.

  • More specific error messages from DGEList() when invalid (NA, negative or infinite) count values are detected.

  • Bug fix to glmfit.default() when lib.size is specified.

  • Bug fix to column name returned by decideTestsDGE().


Changes in version 1.9.1:

  • fixed: a minor bug to allow users generate EGSEA reports for only a single base method

  • fixed: several minor bugs

  • Change: from biocLite to BiocManager


Changes in version 1.0.0:

  • user can now supply her/his/its own colour vector to label the points

  • default is to now draw grid lines and only have left and bottom borders

  • when selectLab is not NULL, even variables that do not pass the thresholds are now labelled along with those that do, even when DrawConnectors is either TRUE or FALSE.

  • correctly catches non-numeric x and / or y variables, and throws error.

  • the function now tolerates P values of 0 (zero) and replaces these with the lowest possible double value, given a user’s specific computer architecture and R version.


Changes in version 1.11.1:

  • add as.normalizedMatrix() function to convert a matrix to normalizedMatrix class


Changes in version 2.12.0:

  • Major refactoring of ID mapping for the rownames of a SummarizedExperiment: (functions idmap / probe2gene): - to.ID can also be a rowData column to support user-defined mappings - support of data-driven strategies for many:1 and 1:many mappings - synchronized behavior of microarray probe ID mapping (probe2gene) and general gene ID mapping (idmap)

  • Alternative representation of gene sets based on GSEABase::GeneSet and GSEABase::GeneSetCollection to facilitate gene ID mapping for gene sets (function getGenesets)

  • Output destination of HTML reports (functions eaBrowse / ebrowser): extended control via arguments out.dir and that overwrite corresponding config defaults (configEBrowser)

  • Separation of nominal and adjusted p-values in DE and EA result tables (functions deAna / sbea / nbea)


Changes in version 2.5.9:

  • Write the official scientific name into the “Organism” metadata field.

Changes in version 2.5.8:

  • Further improve MySQL support and performance.

Changes in version 2.5.6:

  • Add additional (integer) ID columns to the tables for the MySQL backend to improve performance.

  • Use integer primary key columns for join queries in MySQL/MariaDB EnsDb databases.

Changes in version 2.5.5:

  • Switch from RMySQL to RMariaDB.

Changes in version 2.5.2:

  • Switch from GenenameFilter to GeneNameFilter for AnnotationHub >= 1.5.2.

Changes in version 2.5.1:

  • Fix bug in getGeneRegionTrackForGviz that throws an error if both protein coding and non-coding transcripts are fetched.


Changes in version 1.24.0:


  • add support for Ensembl release 94 (this should also encompass 93)


Changes in version 0.99.8:

  • Fix a bug in calling BiocParallel

Changes in version 0.99.7:

  • Code improvements

Changes in version 0.99.5:

  • Increase font sizes in plots

  • Add line of mean DEG discovery in interect plot

  • Improve clarity in plots

  • Vignette receives major edits to improve clarity

Changes in version 0.99.4:

  • Update installation instruction in vignette

Changes in version 0.99.3:

  • Add additional citations

  • Reduce example runtime with fewer combinations

Changes in version 0.99.2:

  • Remove set.seed from package code

Changes in version 0.99.0:

  • Codes ready for bioconductor submission

  • Added full example dataset

  • Cleanup the outputs to be more descriptive and append ERSSA_ to all files

  • Write vignette


Changes in version 1.7.3:

  • vignette: use print rather ‘knit_print.ggvis’

  • ggvis: include transparency, fix issue position legend

  • rbokeh: use vector instead of column names for ly_hexbin

Changes in version 1.7.2:

  • ggplotEsetPlot: enable title/axes labels of type expression

Changes in version 1.7.1:

  • fix issue duplicated columns when same column is used for multiple aesthetics (reported as issue in ggplot2:


Changes in version 2.0:

  • Minor bugs fixed (ClassifyEvents)

  • Relative error is now obtained when obtaining PSI

  • New statistical analysis based on PSI and the associated relative error

  • New pipeline for RNA-Seq based on quantification using a reference transcriptome

  • Multi-path events detection o Events with more than two alternative paths are detected


Changes in version 0.99.13:

  • Fixed bugs that would cause ExCluster to either crash or not properly plot results in some cases

Changes in version 0.99.12:

  • Loosened FDR calculations slightly (ExCluster was a bit too stringent)

  • Added plot.Type option to plotExonlog2FC function, which accepts “bitmap” and “PNG”

  • Bug-tested plot.Type so machines with at least Ghostscript or X11 forwarding will have minimal issues

  • Changed how files/folders are written & how write-permissions are detected, to avoid bugs

  • Updated the vignette to use BiocManager instead of biocLite

Changes in version 0.99.11:

  • Removed some duplicated code (stripping ID numbers, computing p-values)

  • removed several instances of cat() and print() and replaced them with message()

  • changed apply() code to use matrixStats instead, which is up to 500 times faster (Thanks Lori!)

  • this previous change sped the algorithm up from 1 hour+ to only ~ 20 minute runtime

  • changed the test dataset so one of the genes has a p-value < 0.05 and plots results

Changes in version 0.99.10:

  • The GFF_convert function now outputs GFF3 formatted annotations

  • Amended other functions (processCounts, ExCluster) to work on GFF3 formatted annotations

  • Changed the output of GFF_convert to be a GRanges object of said GFF3 annotations

  • Created a separate, internal, load_ExCluster_functions.R script to load helper functions

  • Removed many depenencies on variables outside the environment for said functions

  • Created a library of error messages in the ExCluster_errors.R script (internal)

  • Separated the large ExCluster function into ExCluster.R, ExClust_compute_stats.R, and ExClust_main_function.R

Changes in version 0.99.9:

  • Added the function rtracklayerGTFtoGFF, which flattens GTF files imported by rtracklayer to GFF format

  • Added the function GRangesFromGFF, which converts GFF formatted data to GRanges format

  • Added the function GRangesFromExClustResults, which converts ExCluster function results to GRanges format

  • Removed repeated code from the GFF_convert function

  • Most functions now have checks to ensure GTF, GFF, and ExClustResults data is formatted correctly’

  • Made an improvement to the processCounts function, which handles some edge cases better (zero reads in some conditions)

Changes in version 0.99.8:

  • Fixed build check errors from 0.99.7

Changes in version 0.99.7:

  • Fixed a number of bugs resulting from ExCluster() function code changes

  • Updated the Vignette to correctly reflect changes suggested from the Bioconductor review

  • Added several package imports to better keep track of global variables/functions

  • Reduced the lengths of code lines in a number of instances

  • Cleaned up error messages for ExCluster() function

Changes in version 0.99.6:

  • Completely re-wrote the GFF_convert() function to have helper functions and take advantage of GenomicRanges

  • Changed processCounts, which was incorrectly counting reads as stranded (is now set to unstranded)

  • Altered ExCluster null hypothesis simulations to run faster (about 4 times faster now)

  • Made numerous small changes to address the issues with first Bioconductor review

Changes in version 0.99.5:

  • Fixed incorrectly pushed changes, which caused build error

Changes in version 0.99.4:

  • Reformatted the Vignette & DESCRIPTION to process the Vignette correctly with Sweave

Changes in version 0.99.3:

  • Removed extraneous files causing errors in the build

Changes in version 0.99.2:

  • Reformatted the Vignette & DESCRIPTION to process the Vignette correctly with Sweave

Changes in version 0.99.1:

  • Removed extraneous files causing errors in the build

Changes in version 0.99.0:

  • ExCluster package now passes R CMD build and check, and BiocCheck!

  • takes about 2-3 hours to run on large datasets

  • added a “Toy Dataset” for function manual runnable examples within the package

  • more code in ExCluster has been turned into functions to reduce repeated code

  • still some repeated code (such as parsing EnsIDs and exon bins)


Changes in version 1.7.0:


  • There are now validity checks for tags (valid biocViews in DESCRIPTION), RDataPath (must be defined), SourceUrls (must be defined and indicate url), genome (valid length), sourcetype (from list of valid entries), species and taxonomy id (validated from GenomeInfoDbData)


  • Modified to use BiocManager instead of BiocInstaller


Changes in version 1.1.6:

  • Fixed vignette indices

Changes in version 1.1.5:

  • Added full vignette on the zebrafish dataset

  • Small modifications to the Mus musculus vignette

Changes in version 1.1.4:

  • Added a full vignette showing a case study on Mus musculus

  • Functions getCom and getGraph are exported now

  • Added DT and other packages to suggests

  • Small fixes for BiocCheck

Changes in version 1.1.3:

  • Version 1.1.2 did not skip such test

Changes in version 1.1.2:

  • Disabled buildGraphFromKEGGREST test in 32-bit Windows due to its memory usage


Changes in version 3.15:

  • plotKegg() has been deprecated. It will be removed from the package in upcoming versions.


Changes in version 1.7.1:

  • Setting colwidth to zero make column not to be drawn

  • Changable line width in plotEnrichment


Changes in version 1.10.1:

  • add parallel processing compatibility


Changes in version 1.19.1:

  • Changed how NEWS is displayed.

Changes in version 1.19.0:

  • Same as previous. Bumped by BioConductor.


Changes in version 0.99.10 (2018-09-27):

  • Support for MgsaSets object (mgsa package) added

Changes in version 0.99.9:

  • Documentation update

Changes in version 0.99.8:

  • Man pages list shortened to 10 pages

  • Documentation update

Changes in version 0.99.7 (2018-07-19):

  • Argument specifying column with Gene IDs added to GAFReader class

  • Example gaf file truncated (don’t use it for real analysis!)

Changes in version 0.99.6 (2018-07-19):

  • Malformed description filed problem fixed

  • Imports for stats and methods packages added

Changes in version 0.99.5 (2018-07-16):

  • R version dependency changed from version 3.4.4 to 3.5

Changes in version 0.99.4 (2018-07-16):

  • Vignettes update: less chunks with eval=FALSE

  • /data added to .Rbuildignore

Changes in version 0.99.3 (2018-07-13):

  • Vignettes update

  • Bugs with documentation fixed

  • R CMD check with no warnings

Changes in version 0.99.2 (2018-07-12):

  • Subscribed to the bioc-devel mailing list.

Changes in version 0.99.1 (2018-07-12):

  • .Rproj file removed from repository

Changes in version 0.99.0 (2018-07-12):

  • Submitted to Bioconductor


Changes in version 1.17.1-1.17.6:


  • new options ‘recursive’ and ‘include.dirs’ in ls.gdsn(): the listing recurses into child nodes


  • replace BiocInstaller biocLite mentions with BiocManager

  • digest.gdsn() fails if the digest package is not installed

  • SIMD optimization in 2-bit array decoding with a logical vector of selection (3x speedup when there are lots of zeros)


  • bug fixed: put.attr.gdsn() fails to update the existing attribute


Changes in version 0.99.13 (2018-08-02):

  • Improved the code to include more from tidyverse; simplified code

  • Using now roxygen2 to create Namespace and importing each function indiviually

  • Created a NEWS.Rd file parsable by utils::news in folder inst


Changes in version 1.64.0:


  • Add na.rm = to row/colttests, requested by


Changes in version 1.23.2:

  • Fix the problem for when the interaction network is breaking.


Changes in version 2.12.0:

  • pcair and pcrelate have been completely rewritten for better consistency with other methods. Some argument names have changed; see the documentation. The output of pcrelate is now a list of data.frames instead of a list of matrices.

  • pcrelateReadKinship and pcrelateReadInbreed are deprecated, as these tables are now returned by pcrelate.

  • pcrelateMakeGRM is deprecated; use pcrelateToMatrix with new pcrelate output format.

  • king2mat is deprecated; use kingToMatrix instead.

  • fitNullMM, fitNullReg, assocTestMM, and admixMapMM are deprecated. assocTestSeq and assocTestSeqWindow are defunct. Use fitNullModel, assocTestSingle, assocTestAggregate, and admixMap instead.

Changes in version 2.11.15:

  • Refactor pcrelate.

Changes in version 2.11.14:

  • Added assocTestAggregate method for GenotypeData objects.

Changes in version 2.11.11:

  • Refactor pcair.

Changes in version 2.11.8:

  • Added admixMap function to replace admixMapMM.

Changes in version 2.11.4:

  • Added assocTestSingle and fitNullModel methods for GenotypeData objects.


Changes in version 1.18.0


  • Add checkCompatibleSeqinfo().


  • Update genomeMappingTbl.csv, the db used internally by genomeBuilds() and family.


Changes in version 1.5.8:

  • filters are now chainable with pipes


Changes in version 1.34.0:


  • 2 changes to makeTxDbFromGFF() / makeTxDbFromGRanges(): + Now they support GFF3 files where the CDS parent is an exon instead of a transcript. Note that such GFF3 files are rare and not following the well established convention documented in the GFF3 specs: + Now they accept missing/invalid CDS phases (with a warning).

  • makeTxDb() now accepts missing CDS phases.


Changes in version 1.18.0:


  • (v. 1.17.3) Add vcfFields,VcfStack-method.


Changes in version 1.34.0:


  • Add coercions from GenomicRanges to IRangesList and from GenomicRanges to CompressedIRangesList. These 2 new coercions are equivalent to coercion from GenomicRanges to IntegerRangesList, that is, if ‘gr’ is a GenomicRanges object, the 3 following coercions are equivalent and return the same CompressedIRangesList object: as(gr, “IntegerRangesList”) as(gr, “IRangesList”) as(gr, “CompressedIRangesList”)


  • Deprecate several RangedData methods: seqinfo, seqinfo<-, seqnames, and findOverlaps#RangedData#GenomicRanges

    + RangedData objects will be deprecated in BioC 3.9 (their use has been
    discouraged since BioC 2.12, that is, since 2014). Package developers
    that are still using RangedData objects need to migrate their code to
    use GRanges or GRangesList objects instead.


  • Make [[, as.list(), lapply(), and unlist() fail more graciously on a GenomicRanges object.

  • Make “show” methods for GenomicRanges and GPos objects robust to special metadata column names like “stringsAsFactors”.

  • Export the “update” method for GRanges objects. This addresses


Changes in version 1.6.0:


  • Functions and classes deprecated in the previous release (scores, MafDb class) have been now removed from the package.

  • Added support to latest release 2.1 of gnomAD MAF data, stored in packages MafDb.gnomAD.r2.1.hs37d5 and MafDb.gnomADex.r2.1.hs37d5.


Changes in version 1.9 (2018-10-20):


  • Bayesian hierarchical model implemented => multiple comparison solved

  • Transition from effect size metrics to GLMs

  • Posterior predictive checks automatic

  • Retrospective power analysis available

  • Stan model debugging possible

  • Multicore speedup

  • Phylogenetic bias quantification

  • Data reduction with diagnostics procedure based on random forest

To do

  • Include a CONFIG file to change internal parameters

  • Add practical examples where genphen has been used.

  • Implement modules for data augmentation

  • Update todo after data augmentation


Changes in version 3.43.1:

  • man page links modernized

  • vignette to Rmd

  • Warning added to vignette indicating that gQTLBase/gQTLstats are more modern


Changes in version 4.0.0:

  • new function ‘gGlobalAncova’ for generalized linear models: groups of tested variables can be quantitative, categorical, ordinal and even of mixed types

  • new function ‘Plot.features’ for showing contributions of individual variables to global test statistic; equivalent to ‘Plot.genes’, but for ‘gGlobalAncova’

  • new function ‘gGlobalAncova.hierarchical’ for hierarchical testing.

  • new S4-class ‘GAhier’ for storing results of gGlobalAncova.hierarchical

  • new methods ‘show’, ‘results’, ‘sigEndnodes’, and ‘Plot.hierarchy’ to access and visualize results from ‘GAhier’ objects

  • added CITATION and NEWS files

  • Vignettes are now created with knitr


Changes in version 1.1.5:


  • add name and domain to categories in get_anno_categories()

  • update GO-graph (version 11-Oct-2018)

Changes in version 1.1.2:


  • allow for custom gene coordinates (alternative to default Bioconductor annotation packages; coordinates are used when the familiy-wise error rate is corrected for gene length or spatial clustering of genes)


  • gene coordinates used in correction for gene-length or spatial clustering are not restricted to chromosomes 1-22,X,Y,MT anymore


Changes in version 1.0.0:


  • Add new functions, BigLD, CLQD, GPART, LDblockHeatmap, convert2SumExpObj


Changes in version 1.27.6 (2018-10-25):

  • Updated all pathway data.

  • Added PathBank database.

Changes in version 1.27.2 (2018-05-22):

  • Vignette describing mixed analysis with genes and metabolites.


Changes in version 1.13.2:

  • add_rect_track(): height is not converted to mm anymore


Changes in version 1.27.1:

  • Add GenotypeIterator and GenotypeBlockIterator classes. These classes allow returning blocks of SNPs with each call to iterateFilter.


Changes in version 1.10.0:


  • Implement the TENxMatrix container (DelayedArray backend for the HDF5-based sparse matrix representation used by 10x Genomics). Also add writeTENxMatrix() and coercion to TENxMatrix.


  • By default automatic HDF5 datasets (e.g. the dataset that gets written to disk when calling ‘as(x, “HDF5Array”)’) now are created with chunks of 1 million array elements (revious default was 1/75 of ‘getAutoBlockLength(x)’). This can be controlled with new low-level utilities get/setHDF5DumpChunkLength().

  • By default automatic HDF5 datasets now are created with chunks of shape “scale” instead of “first-dim-grows-first”. This can be controlled with new low-level utilities get/setHDF5DumpChunkShape().

  • getHDF5DumpChunkDim() looses the ‘type’ and ‘ratio’ arguments (only ‘dim’ is left).


Changes in version 1.17.1:

  • new function hlaDistance()


Changes in version 1.11.1:

  • move IRanges and GenomicRanges to imports field in DESCRIPTION


Changes in version 1.1.2 (2018-09-07):

  • Adding gene name to tooltip

  • Fixing minor bugs in chart.R, save.R, stats.R

Changes in version 1.0.1 (2018-06-14):

  • Fixing minor bug in heatmap_plot about variances in case variable_cluster = TRUE.

  • Fixing minor bug in visualize_report.

  • Adding test_package.R file.


Changes in version 0.99.19:

  • Minor change: - Update CITATION

Changes in version 0.99.18:

  • Minor changes: - Add ‘journal’ to CITATION - Add ‘+ file LICENSE’ to DESCRIPTION

Changes in version 0.99.17:

  • Minor changes: - Standardize the NEWS file - Add CITATION file

Changes in version 0.99.16:

  • Minor changes: - Update License. Now use GPL-3 instead of MIT.

Changes in version 0.99.14:

  • Minor changes: - Replace visType == ‘all’ in hpaVis() with identical(visType, ‘all’) - Replace extractType == ‘all’ in hpaXml() with identical(extractType, ‘all’)

Changes in version 0.99.13:

  • Respond to Bioconductor review on Aug 6, 2018

  • Minor changes: - Fix example for hpaXml() (issue #5) - Update documentation for hpa_downloaded_histology_v18 dataset (issue #6) - Re-name R/data.R to R/hpa_downloaded_histology_v18.R (issue #7) - Cross-reference documentations (issues #8, #9) - Combining hpaListParam() and hpaSubset() on one man page (issue #10)

Changes in version 0.99.12:

  • Minor changes: - Minor edit in hpaXml() function

Changes in version 0.99.11:

  • Respond to Bioconductor review on Jun 11, 2018

  • Major changes: - Add the hpaVis() function as an umbrella for the whole function family - Add the hpaXml() function as an umbrella for all XML extraction

  • Minor changes: - Remove the ignore/ directory - Import individual functions for xml2 - Remove /dontrun{} on man pages - Modifications to hpaVis functions for better consistency - Updated the help files with details about output of each function

Changes in version 0.99.10:

  • Initital version reviewed by Bioconductor


Changes in version 1.23.3:

  • Use BiocManager for installation <2018-07-19 Thu>

Changes in version 1.23.2:

  • Rename 16.1 objects <2018-05-23 Wed>

Changes in version 1.23.1:

  • New Bioconductor devel

  • Update to HPA version 18


Changes in version 0.99.3:


  • updated R functions to use stopifnot() for error control

  • changed cat() to message() for communicating output

  • change use of R CRAN parallel functions to BiocParallel

  • replace date field with hard-corded date in vignette

  • update variable names to lower snake case in vignette

  • added new biocViews (RNASeq, Software, StatisticalMethod, FeatureExtraction)


Changes in version 0.23.2 (2018-07-18):


  • The readIDAT() function gains a ‘what’ argument (only for unencrypted IDAT files). This allows the fast return of the number of ‘nSNPsRead’ (number of probes in file) and ‘IlluminaID’ (probenames). This is to allow fast handling of IDAT files in the minfi package.

Changes in version 0.23.1 (2018-07-18):


  • ROBUSTNESS: Now registering native routines.

Changes in version 0.23.0 (2018-05-01):


  • The version number was bumped for the Bioconductor devel version, which is now BioC v3.8 for R (>= 3.5.0).


Changes in version 1.13.3:


  • additional variant of t-mixture model fitting respecting truncated observed values


  • minor bugfixes and code cleaning


Changes in version 1.10.0:

  • Bug fix to seqinfo<- to support other arguments in the generic.

  • Modified behaviour of inflate() with unspecified fill= for GInteractions objects.


Changes in version 1.5.2:


  • buildSsTypePwms() function supports the possibility to select begin and end point of splice sites sequences from which PWMs are built. It also supports the possibility to paste splice sites to build PWM.


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

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

  • buildSsTypePwms() corrected and modified to better suit data for all species from SpliceRack and U12DB.


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 1.6.2:

  • Updated the function getNormalizedResponse() to prevent NAs

Changes in version 1.6.1:

  • Added installation script and installation description in vignette


Changes in version 2.16.0


  • Optimize unlist() on Views objects.

  • Optimize range(), any() and all() on CompressedRleList objects.

  • Optimize start(), end(), width() setters on CompressedRangesList objects.


  • Deprecate several RangedData methods: + score, score<-, lapply, within, countOverlaps; + coercions from list, data.frame, DataTable, Rle, RleList, RleViewsList, IntegerRanges, or IntegerRangesList to RangedData. + RangedData objects will be deprecated in BioC 3.9 (their use has been discouraged since BioC 2.12, that is, since 2014). Package developers that are still using RangedData objects need to migrate their code to use GRanges or GRangesList objects instead.

    • The RangesList() constructor is now defunct (after being deprecated in BioC 3.7).


  • Fix DF[IRanges(…), ] on a DataFrame with data.frame columns.

  • Make [[, as.list(), lapply(), and unlist() fail more graciously on a IRanges object.

  • NCList objects now properly support c().


Changes in version 1.1.13:

  • Add missing observer for assay type in row data plot panels.

  • Add missing observer for colorpicker when colouring by feature name in row-based plots, or by sample name in column-based plots.

  • Ignore NA values when computing the range of coloring scales.

  • Add a size expansion factor (5x) to the selected point when colouring by feature name in row-based plots, or by sample name in column-based plots.

  • Fix redundant coloring of selected point when colouring by feature name in row-based plots, or by sample name in column-based plots.

  • Update basic vignette.

Changes in version 1.1.12:

  • Updated NEWS file.

Changes in version 1.1.11:

  • Export list of panel names and codes.

Changes in version 1.1.10:

  • Fix colour scale to be invariant when selecting on a different color.

  • Protect heat map plot panels against restriction on zero samples.

Changes in version 1.1.9:

  • Fix compatibility with DelayedArray assays.

Changes in version 1.1.8:

  • Extend unit test coverage.

  • Move generics to separate file.

  • Minor fix to annotateEnsembl.

  • Update list of functionalities in README.

Changes in version 1.1.7:

  • Resolved BiocManager message.

Changes in version 1.1.6:

  • Minor fix for Windows unit test.

Changes in version 1.1.5:

  • New panel colors.

  • Control arguments to custom panels through action buttons.

  • Distinguish visible from active arguments for custom panels.

Changes in version 1.1.4:

  • Split ?defaults help page by panel type.

  • Generalized support for custome data plots and statistics tables.

Changes in version 1.1.3:

  • Add new Sample assay plot panel type.

  • Extend documentation.

  • Split vignette into three: basic, advanced, ExperimentColorMap.

  • Fix initialization of reduced dimensions with a single plot axis choice.

  • Substitute discouraged use of sapply.

  • Moved roxygen importFrom instructions closer to the relevant code.

  • Increase unit test coverage.

  • Consistent use of “colormap” through the package.

  • Update installation instructions.

  • Add CITATION file.

  • Add Figure 1 of article in README.

Changes in version 1.1.2:

  • Enable faceting by row and column, with appropriate updates to brush and lasso.

  • Enable shaping on data points.

  • Minor fix of jitter for violin and square plots.

  • INTERNAL: Enable storage of additional beyond X and Y in all.coordinates. See constant .allCoordinatesNames. Necessary for correct behaviour of brushes on faceted plots.

Changes in version 1.0.1:

  • Rename feature expression plots to feature assay plots, for generality.


Changes in version 0.1.27:

  • prepare for Biocoductor submission


Changes in version 1.3.10:

  • A problem was fixed with the isoformSwitchTestDEXSeq() which could cause continuous co-variables to interpreted as discrete co-variables.

  • importRdata() was updated to be a bit more versetile with regards to accepting isoform_ids as row.names.

  • Both isoformSwitchTestDRIMSeq() and isoformSwitchTestDRIMSeq() was updated so the the resulting “isoformSwitchAnalysis” entry in the switchAnalyzeRlist also contains results with p-values set to NA. (NA filter removed). Furthemore the interpretation of design matrixes with regards to continous or discrete variables was improved.

  • The vignette was updated all around including the FAQ sections:

  • “What Quantification Tool(s) Should I Use?”

  • “What constitue an independent biological replicate?”

  • An error message was corrected to give the rigth error

  • various small updates

Changes in version 1.3.9:

  • Update to namespace to fix 1.3.8 update of importCufflinksFiles

  • Update to vignette to fix header

Changes in version 1.3.8:

  • Update to importCufflinksFiles to make it faster and more robust.

Changes in version 1.3.7:

  • isoformSwitchTestDEXSeq() was updated to use testForDEU instead of nbinomLRT as now reccomended by the authors.

Changes in version 1.3.5:

  • One-line summary: Improved robustness, usability and speed

  • Main changes:

  • isoformSwitchTestDEXSeq() is introduced as the new default test as it is a more robust and much more reliable test for differential isoform usage.

  • The original isoformSwitchTest() is decommissioned due to it being inferior to both isoformSwitchTestDEXSeq() and isoformSwitchTestDRIMSeq() in most aspects.

  • importIsoformExpression() now also support import of StringTie quantifications.

  • updates that allows for better handling of Ensemble data.

  • updates throughout the R package making IsoformSwitchAnalyzeR (much) faster and more reliable.

  • Specifically the changes in inlcuded functions are:

  • isoformSwitchTestDEXSeq() is introduced as the default switch isoform switch test function

  • I handles the False Discovery Rate much better

  • It allows for batch corrected effect size estimation

  • It is a good deal faster (for smaller sample sizes)

  • isoformSwitchTestDRIMSeq() was updated to handle continous co-variates.

  • isoformSwitchTest() has been removed from the package since it is obsolte.

  • The importRdata() now:

  • Allows for import via either replicate abundance or replciate count data (or both - which is highly reccomended).

  • These changes were reflected in createSwitchAnalyzeRlist()

  • Test for full rank of experimental design

  • The importCufflinksCummeRbund() and importCufflinksFiles() now also extract and replicate isoform abundance estimates.

  • The functions importRdata(), importCufflinksCummeRbund() and importCufflinksFiles()

  • Calculates isoform fractions based on the replicate isoform fraction matrix (instead based on average isoform and gene expression) providing more accurate estimataes.

  • Was uptimized so they are more streamlined and faster.

  • importGTF (also used by importRdata() ) was updated to handle the problems with version numbering in amongst other Ensembl data.

  • To support the batch correction feature in isoformSwitchTestDEXSeq() the subsetSwitchAnalyzeRlist() function was modified so when subsetting in the the exon entry of the switchAnalyzeRList, as well as any replicate matrix entry (counts, abundances or isoform fractions), all isoforms from genes where at least one isoform passed the filters are kept.

  • The isoformToIsoformFraction() - a general purpose function for calculateing Isoform Fraction (IFs) from isoform expression - are introduced

  • The isoformToGeneExp() function was updated to be true general purpose (less stringent about data formating) and thanks to a tidyverse solution to the central problem is now between 2x-10x faster than previously (and becomses faster as the large the datasets are)

  • createSwitchAnalyzeRlist() was updated to

  • handle replicate data

  • fix condition name problems

  • test for full rank of design

  • importIsoformExpression() was updated to:

  • Support StringTie data.

  • Perform the inter-library normalization after a lenient expression cutoff have beeen applied (to remove most very lowly expressed isoforms).

  • Now uses the “scaledTPM” instead of “lengthScaledTPM” tximport option when imporitng with countsFromAbundance=TRUE The ignoreAfterBar argument from tximport() is now also supported.

  • We introduce the removeAnnoationData() function which eables removal of biological sequence and/or the replicate quantification data from a switchAnalyzeRlist threby significantly removing the size.

  • The default on the IFcutoff in switchPlot() and switchPlotTopSwitches() was updated to 0.05 which should result in cleaner plots (meaningisoforms only contributing minimally to the parent gene expression are now omitted from plot).

  • Specifically the package maintenance changes are:

  • All around speed improvements mainly due to updates regarding two bottelnecks:

  • stringr::str_c replaces paste0 since it is up to 10x faster on data.frames

  • dplyr::inner_join() or dplyr::left_join() have replaced most base::merge() opperations since since they are up to 10x faster.

  • All documentation and examples are now based on Salmon data. Cufflinks is shown as a special case.

  • For this switch new example data was included in the package.

  • Directy suppor of Cufflinks/Cuffdiff files via the cummeRbund R package (via the importCufflinksCummeRbund function) have been removed. Use importCufflinksFiles() instead.

  • analyzeSignalP, analyzePFAM, analyzeCPAT now better handles empty files.

  • All documentation regarding PFAM was updated to use EBI’s homepage (and their restrictions).

  • Updated package title to reflect the introduction of the alternative splicing module

  • A requirement for tximport >= 1.8.0 was introduced (due to problems with importing from RSEM in previous versions)

  • Highligting that import of GTF files can be done from both unziped and gziped gtf files.

  • Updated NEWS file to follow bioconductor style guideline

  • Genral update to support condition (and covariate) names compatible with model building in R.

  • All general support functions (potentially) used more than once place were moved to tool.R and names were streamlined.

  • Various updates in vignette to reflect all changes desribed above as well as update of installation instructions.

  • Various updates to input testing to catch commonly occuring problems.

  • Correction of loads of spelling mistakes kindely pointed out by @afonsoguerra - thanks!


Changes in version 1.9.5:


  • Fix NEWS format

Changes in version 1.9.4:

  • Support object creation from rawData of a current IsomirDataSeq object.

Changes in version 1.9.3:

  • Fix warnings in dosc.

Changes in version 1.9.2:

  • Fix bug that quantify wrongly the reference sequence.

Changes in version 1.9.1:


  • Improve clustering in isoNetwork plot.

  • Use varianceStabilizingTransformation to normalize counts.

  • Use a less common column as ID for samples in isoPLot fns.

  • Add updateIsomirDataSeq to be compatible with previous versions.

  • Adapt all functions to new object. Fix documentation.

  • Reduce object size and structure


Changes in version 1.0.0:

  • New package kmknn, for k-means-based k-nearest neighbor detection.


Changes in version 3.38.0:

  • New function plotExonJunc() to plot results from diffSplice().

  • New function logsumexp().

  • New argument hl.col for volcanoplot(), allowing users to specify the color for the gene names when highlight > 0.

  • barcodeplot() no longer assumes that ‘statistic’ has unique names. Previously it returned an error if names(statistic) contained any duplicated values.

  • The colors “blue”, “red” and “yellow” used by coolmap() changed to “blue2”, “red2” and “yellow2” when used in a color panel with white.

  • goana.Rd now explains more explicitly that p-values are unadjusted for multiple testing.

  • arrayWeights.Rd now mentions minimum dimensions for expression object.

  • More advice on how to choose ‘lfc’ added to the treat() help page.

  • Minor bug fix to the mixed p-value from roast() and mroast() when set.statistic=”floormean”.

  • Bug fix for cumOverlap(), which was under-counting overlaps in some cases.


Changes in version 0.99.17:

  • Error is occured when the OS is windows?

Changes in version 0.99.16:

  • inst/LRBasePkg-template/man/@PKGNAME@.Rd is modified

Changes in version 0.99.15:

  • Reviewed

Changes in version 0.99.14:

  • vignette is modified

Changes in version 0.99.13:

  • vignette is modified

Changes in version 0.99.12:

  • vignette is modified

Changes in version 0.99.11:

  • vignette is modified

Changes in version 0.99.10:

  • Removed inst/doc and added vignettes

Changes in version 0.99.9:

  • Removed vignettes

Changes in version 0.99.8:

  • Added inst/doc

Changes in version 0.99.7:

  • Added inst/doc

Changes in version 0.99.6:

  • rm -rf inst/doc

Changes in version 0.99.5:

  • Added VignetteBuilder and VignetteEngine

  • The vignette set as BiocStyle

Changes in version 0.99.4:

  • The vignette-related files (.Rmd/.html) in vignettes directory are moved to inst/doc direcotry

Changes in version 0.99.3:

  • The vignette-related files (.Rmd/.html) in inst/doc directory are removed

Changes in version 0.99.2:

  • The vignette-related files (.Rmd/.html) in inst/doc directory are removed

Changes in version 0.99.1:

  • The vignette-related files (.Rmd/.html) in inst/doc directory are removed

Changes in version 0.99.0:

  • Package released


Changes in version 1.8.0:


  • OncogenicPathways - Perform enrichment for known oncogenic pathways from TCGA studies.

  • PlotOncogenicPathways - Plots OncogenicPathways results

  • drugInteractions - Drug gene interactions from DGIB database.


  • trinucleotideMatrix functions now works with BSgenomes instead of time consuming fasta files

  • rainfallPlot now detects Kataegis based on a greedy algorithm


Changes in version 1.1.9:

  • Add parameter ‘pathway_limit’ / ‘limit’ / ‘gmtpath’ in FluteRRA, FluteMLE, and all enrichment functions which enable users to customize gene sets for enrichment analysis.

  • Remove DAVID and GOstats, which are not recommended.

  • Add enrichment score in enrichment results from all algorithms.

Changes in version 1.1.6:

  • Add functions to plot figures in NatureProtocol manuscript.

  • Shorten the check time.

  • Remove null figures in pathview part.

Changes in version 1.1.1:

  • Speed up the enrichment analysis.

  • Release memory in time.


Changes in version 1.7.6:


  • Added ‘apply’ methods for ‘sparse_mat’ and ‘virtual_mat’

  • Added ‘vm_used’ function to exported internal utilities

  • Can infer length of ‘matter_vec’ from paths when missing

  • Can coerce ‘matter_list’ to ‘matter_matc’ or ‘matter_matr’ if all elements of the list are the same length


  • Initializing a matter object with data to an existing file no longer results in a warning if ‘filemode’ is supplied


  • Fixed bug where subsetting ‘sparse_mat’ objects would pull ‘matter_list’ key-value pairs into memory

  • Subsetting ‘sparse_mat’ objects with out-of-bounds subscripts when ‘drop=NULL’ is now an error

Changes in version 1.7.5:


  • Added ‘as.matrix’ methods for ‘sparse_mat’ and ‘virtual_mat’

Changes in version 1.7.4:


  • Added coercion from ‘matter_mat’ to ‘matter_list’

Changes in version 1.7.3:


  • Added ‘rep_vt’ class for virtual replicated vectors

Changes in version 1.7.2:


  • Updated installation instructions for BiocManager

  • Setting ‘sparse_mat’ keys also updated nrows/ncols


  • Fixed mem() to reflect R >= 3.5 gc() function

Changes in version 1.7.1:


  • Fixed file.exists() bug when length(paths) > 1


Changes in version 1.7.1:

  • add citation <2018-05-25, Fri>


Changes in version 1.11.3 (2018-10-22):

  • adjust NEWS file to new format according to ?news: o entries are grouped according to version, with version header “Changes in version” at the beginning of a line, followed by a version number, optionally followed by an ISO 8601 format date, possibly parenthesized o entries may be grouped according to category, with a category header (different from a version header) starting at the beginning of a line o entries are written as itemize-type lists, using one of o, *, - or + as item tag. Entries must be indented, and ideally use a common indentation for the item texts

Changes in version 1.11.2 (2018-10-15):

  • remove Makefile from directory vignettes/

  • check if package passes R CMD build and R CMD check without any error messages and vignette can be run without any errors


Changes in version 1.3.1:


  • New citation referring to the associated published article in Nucleic Acids Research.


Changes in version 1.5.1:


  • New citation referring to the associated published article in Nucleic Acids Research.


Changes in version 1.7.10:


  • update man: update object and function descriptions to resolve the ‘file link treated as topic’ warning under windows

Changes in version 1.7.9:


  • bug fix: make internal function .checkdbdir more error proof

Changes in version 1.7.8:


  • internal applyTbxByOverlap(): did not work correctly for return.type set to “data.frame” or”data.table”, due to missing argument.

Changes in version 1.7.7:


  • unite(): skip checking if destranded tabix file exist

Changes in version 1.7.6:


  • methSeg(): introduce parameter initialize.on.subset to subset data for initialization of mixture modeling; update description; add tests

Changes in version 1.7.4:


  • update link to test-file for methSeg() function

Changes in version 1.7.3:


  • selectByOverlap(): update description; refine method signatures to only support GRanges as range argument; update NAMESPACE to import subjectHits() method from S4Vectors

Changes in version 1.7.2:


  • New constructor method methylRawList() can be used to combine list of methylRaw objects into a methylRawList


  • fix bug in methSeg: when joinSegments was activated, diagnostic plot would always be plotted

  • fixes in selectByOverlap() function: update description, to show that any methylKit object (tabix or not) can be used with it ; fixed broken method after @subjectHits was not available anymore

  • fix error in .checkTabixFileExists function, that lead to overwriting of files


Changes in version 0.99.24 (2018-10-22):

  • adjust NEWS file to new format according to ?news: o entries are grouped according to version, with version header “Changes in version” at the beginning of a line, followed by a version number, optionally followed by an ISO 8601 format date, possibly parenthesized o entries may be grouped according to category, with a category header (different from a version header) starting at the beginning of a line o entries are written as itemize-type lists, using one of o, *, - or + as item tag. Entries must be indented, and ideally use a common indentation for the item texts

Changes in version 0.99.23 (2018-10-16):

  • improve createStructuralAdjacency function

Changes in version 0.99.20 (2018-08-06):

  • replace psych::corr.test by WGCNA::corAndPvalue to improve speed

Changes in version 0.99.19 (2018-07-26):

  • print message when model calculation in createStatisticalAdjacency is finished

Changes in version 0.99.18 (2018-07-19):

  • set rfPermute.formula to rfPermute.default in order to use num.cores

Changes in version 0.99.17 (2018-07-19):

  • set num.cores to 1 in test_statistical for randomForest

Changes in version 0.99.15 (2018-07-16):

  • do not import stabsel from stabs

Changes in version 0.99.14 (2018-07-14):

  • use BiocManager instead of BiocLite for installation

Changes in version 0.99.13 (2018-07-12):

  • do not export functions threeDotsCall and addToList

Changes in version 0.99.12 (2018-07-12):

  • use BiocStyle package for vignette

  • remove Makefile

  • use BiocParallel instead of parallel, for instance use bplapply instead of mclapply

Changes in version 0.99.11 (2018-07-03):

  • speed up function rtCorrection by vectorizing

Changes in version 0.99.10 (2018-07-03):

  • speed up function createStructuralAdjacencyMatrix by vectorizing

Changes in version 0.99.9 (2018-06-26):

  • change 1:… to seq_len()

Changes in version 0.99.8 (2018-06-26):

  • implement function rtCorrection

Changes in version 0.99.6 (2018-06-13):

  • use camelCaps for functions

  • use no spaces between ‘=’ and named arguments

  • fix typo in lasso function

Changes in version 0.99.5 (2018-06-12):

  • change 1:… to seq_len()

Changes in version 0.99.4 (2018-06-12):

  • change 1:… to seq_len()

Changes in version 0.99.3 (2018-06-11):

  • remove sum check for correlation

Changes in version 0.99.2 (2018-06-11):

  • require R version >= 3.5

Changes in version 0.99.1 (2018-06-11):

  • remove bugs that there are no WARNINGS and ERRORs when running R CMD check and R CMD BiocCheck

  • reduce file size of peaklist_example.RData

  • submit to Bioconductor

Changes in version 0.99.0 (2018-05-14):

  • implement functionality to calculate statistical models of correlation (Pearson, Spearman), LASSO, Random Forest, Context likelihood or relatedness network algorithm, algorithm for the reconstruction of accurate cellular networks, constraint-based structure learning algorithm

  • implement the function create_statistical_network to calcululate the consensus matrix from the different statistically-infered networks

  • implement the function create_structural_network to calculate molecular weight differences and create a network

  • implement the function combine_structural_statistical to combine the structurally-derived and statistically-derived network

  • implement model partial and semi-partial pearson/spearman correlation using the ppcor package


Changes in version 1.27:

  • v1.27.2 Fix bug in preprocessQuantile() that arose when checking input for previous preprocessing method. Thanks to @DelnazR for the report (<URL:>).

  • v1.27.3 Fixed bug related to switch A and B for SNPs of type I when using convertArray / combineArrays. Reported by Jenny van Dongen.

  • v1.27.3 Fixed error in dmpFinder.

  • Added preliminary support for HorvathMammalMethylChip40.


Changes in version 0.99.28:

  • Update module_biclust function <2018-10-23, Thue>

Changes in version 0.99.27:

  • Update module_NMF function <2018-10-20, Sat>

Changes in version 0.99.26:

  • Update module_biclust function <2018-10-18, Thus>

Changes in version 0.99.25:

  • Update module_NMF function <2018-10-12, Fri>

Changes in version 0.99.24:

  • Update miRSM.R <2018-10-10, Wed>

Changes in version 0.99.23:

  • Update Vignettes <2018-08-31, Fri>

Changes in version 0.99.15-0.99.22:

  • Update R codes, DESCRIPTION, NEWS, README <2018-08-27, Mon>

Changes in version 0.99.8-0.99.14:

  • Update miRSM.Rmd <2018-08-07, Thue>

Changes in version 0.99.4-0.99.7:

  • Update runnable examples <2018-08-06, Mon>

Changes in version 0.99.3:

  • Update src <2018-08-03, Fri>

Changes in version 0.99.2:

  • Update module_biclust function <2018-08-03, Fri>

Changes in version 0.99.1:

  • Change the type of input data into a SummarizedExperiment object. Polish the file miRSM.R. <2018-08-03, Fri>

Changes in version 0.99.0:

  • This is the first version of miRSM package. If any bugs, please let me know. Contact Email: <2018-08-03, Fri>


Changes in version 1.7.5:

  • Update miRsponge.Rmd <2018-08-25, Sat>.

Changes in version 1.7.4:

  • Update netModule function <2018-08-10, Fri>.

Changes in version 1.7.3:

  • Update netModule function <2018-07-31, Tues>.

Changes in version 1.7.2:

  • Update netModule function <2018-07-31, Tues>.

Changes in version 1.7.1:

  • Update netModule function <2018-07-29, Sun>.

Changes in version 1.7.0:

  • Update netModule function <2018-07-27, Fri>.


Changes in version 1.15.2:

  • Updated getMappedEntrezIDs, gometh and gsameth to to speed up execution by taking the array annotation in as an optional argument.

  • missMethyl now uses the latest IlluminaHumanMethylationEPICanno.ilm10b2.hg19 annotation by default for EPIC arrays.

Changes in version 1.15.1:

  • Added getAdjusted function for extracting RUVm adjusted data for visualisation purposes

  • Updated vignette to demonstrate use of getAdjusted function

  • Vignette now includes an example of how to handle cases with RUVm where number of samples is greater than number of Illumina negative controls


Changes in version 1.5.4:

  • Accept DNAString wherever DNAStringSet was accepted.

Changes in version 1.5.3:

  • Fast motif matching Various improvements to improve motif matching speed were implemented. 1. Precomputed position weights to avoid the invokation of the log function during scanning. 2. threshold argument added to avoid having to determine the score distribution for each sequence individually. 3. Stop as soon as the motif score cannot or is certainly exceeding the threshold.

Changes in version 1.5.2:

  • scoreSequence, scoreHistogram, scoreProfile motifHits, motifHitProfile can be used with N-containing sequences. Positions at which the motif overlaps with N’s will be NaN.

  • Background can be computed from a DNAString in addition to a DNAStringSet object.

Changes in version 1.5.1:

  • Background can be computed with sequences that contain N’s.


Changes in version 1.24:


  • query method now flexible, with “andStrings”, “orStrings”, “notStrings” parameters The previous usage style is still supported. See man page.

  • associateTranscriptionFactors (with motifs) substantially faster


Changes in version 1.25.2:

  • fix the bug when plot “others” type of motif.

Changes in version 1.25.1:

  • Fix a bug for y-axis plot.


Changes in version 0.99.0 (2018-08-07):

  • Submitted to Bioconductor


Changes in version 2.7.12:

  • Fix warnings on windows (see #371) <2018-10-26 Fri>

  • Add parameter ppm to consensusSpectrum and meanMzInts (see #373 for details) <2018-10-26 Fri>

Changes in version 2.7.11:

  • Change default for timeDomain in combineSpectra and combineSpectraMovingWindow to FALSE <2018-10-18 Thu>

  • Add new spectra combination function consensusSpectrum <2018-10-24 Wed>

  • Amend plot,Spectrum 1 and 2 (see #369)

Changes in version 2.7.10:

  • Methods for Spectra class <2018-10-15 Mon>

Changes in version 2.7.9:

  • Import rather than depend on BiocParallel <2018-10-15 Mon>

  • Fix failing test on Windows (requiring normalizePath) <2018-10-15 Mon>

Changes in version 2.7.8:

  • MGF exporter gets a new addFields argument (see PR #362) <2018-10-12 Fri>

  • New Spectra (SimpleList of Sepctrum objects) (see PR #361) <2018-10-13 Sat>

Changes in version 2.7.7:

  • Fix unit tests (issue #360, wrong MS OBO CV terms for data smoothing (MS:1000592) and baseline correction (MS:1000593))

Changes in version 2.7.6:

  • Fix wrong MS OBO CV terms for data smoothing (MS:1000592) and baseline correction (MS:1000593).

Changes in version 2.7.5:

  • Add a note about parallel processing in vignette (see #356 for background) <2018-09-04 Tue>

Changes in version 2.7.4:

  • Fix filterMz for spectra with no non-NA intensities in m/z range (see #355) <2018-08-08 Wed>

Changes in version 2.7.3:

  • Fix bug in robust summary (see PR #349) <2018-07-28 Sat>

  • Fix failing unit test <2018-07-28 Sat>

Changes in version 2.7.2:

  • Handle files without any spectra - see #342 <2018-05-15 Tue>

  • New mergeFeatureVars and expandFeatureVars functions <2018-05-30 Wed>

  • Update plot,Spectrum methods to match the tolerance and relative arguments (see #350) <2018-06-29 Fri>

Changes in version 2.7.1:

  • Version bump to force new vignette build

Changes in version 2.7.0:

  • New devel version for Bioc 3.8 # MSnbase 2.6


Changes in version 1.15.1:

  • mzR now added scan number(s) into the table representation of mzIdentML object. As a results it caused an error in my unit test checking if the file reads properly. Fixed this check with updated hash.


Changes in version 1.6.1:

  • Bug fix. For pos/neg switching acquisition two files are can be generated when converting from RAW to mzML (1 for pos, 1 for neg). The resulting files retention time scans were not being tracked properly in msPurity in these cases. This is now fixed. Thanks to Julien ( for spotting the bug.


Changes in version 0.99.0 (2018-09-21):

  • Submitted to Bioconductor


Changes in version 1.11.2:

  • Updated vignette Rmd file to address bug in getGEO to obtain expression data

Changes in version 1.11.1:

  • Updated NEWS file format to reflect changes by version


Changes in version 2.15.5:

  • Fix bug #181

Changes in version 2.15.4:

  • Use new dependency ncdf4 for netCDF reading, removes a lot of build hassles with old libnetcdf-dev linking.

  • specParams returns a numeric scan.number.s.

Changes in version 2.15.3:

  • Adds MS-GF+ information such as Scan Time and a more reliable Scan Number, contributed by FarmGeek4Life (see PR #174).

Changes in version 2.15.2:

  • Add header column ionMobilityDriftTime to report the corresponding CV parameter (issue

  • Ensure ion injection time is always reported in milliseconds.

  • Replace BiocInstaller::biocLite with BiocManager::install (by Bioc core)

Changes in version 2.15.1:

  • Fix typo (see

  • New .hasSpectra and .hasChromatograms private function (see

  • Fix bug in score when more cvParams than expected are read - see <2018-05-26 Sat>

Changes in version 2.15.0:

  • New Bioc devel version


Changes in version 0.99.4:

  • CODE: Modification in the fitModel function to correct the estimations with contrasts specified by the user


Changes in version 0.99.24:

  • Various input checks added

Changes in version 0.99.22:

  • Input parsing corrected so that a clear error message is provided when the design matrix samples doesn’t match the data matrix header

Changes in version 0.99.21:

  • Documentation example fixes

Changes in version 0.99.20:

  • Reactivate quantile normalization

Changes in version 0.99.19:

  • Empty annotation no longer leads to crash when writing output

Changes in version 0.99.17:

  • Very minor fix where function wasn’t retrieved properly from SummarizedExperiment

Changes in version 0.99.16:

  • Crash when feeding SummarizedExperiment as input is fixed

  • If full rows contains only NA values they are filtered and a warning is generated

Changes in version 0.99.15:

  • Corrected expected output from vapply in correlation matrix (where previous varying lengths caused crash)

  • Clearer error message when providing invalid sample/group conditions to statistics module

  • Issue where several identical RT-values caused crash in RT-slicing fixed


Changes in version 1.1.2:

  • bug fix for CZM in RAB plots. if not zeros, plots would fail.

  • updated install instructions to use BiocManager

Changes in version 1.1.1:

  • added slider inputs to change size and opacity of sample names for biplot and coloured biplot

  • changed UI for filtering page

  • added downloadable scripts for PCA biplots, dendrogram/barplots, and effect plots (simple effect plot script).


Changes in version 2.11.1:

  • robustify test.fixation.R, Local max, tolerance


Changes in version 0.99.7:


  • randomisation of batches now implemented via the randBatch helper function

  • updated references

  • updated vignette

Changes in version 0.99.5:


  • replace date field with hard-coded date in vignette

  • updating data.frame rows by group now uses ‘split-apply-combine’

  • vectorise part of the LOND function

  • replace 1:N with seq_len(N)

  • applied consistent formatting & indentation

  • added new tests


Changes in version 2.0.1:

  • Colored edges in sample correlation networks & minor fixes.

Changes in version 2.0.0:

  • Great performance boost by implementation of parallel SOM calculation. “som” package dependence removed.


Changes in version 1.1.12:


  • The orf finding function now find the longest orf per stop codon if you set longestORF = TRUE in findORFS, findMapORFs and findORFsFasta


Changes in version 1.8.1:

  • Update data uploading

  • Modify visualization

  • Add biomarker tab


Changes in version 1.11.2 (2018-06-29):

  • Updated NEWS file of pathVar

  • Updated maintainer email address

Changes in version 1.11.1 (2018-05-15):

  • Updated NEWS file of pathVar


Changes in version 2.8.0:


  • PCA plots now are correctly generated with fixed coordinates


Changes in version 1.11.4:

  • Fix bug in function PrepareAnnotationRefseq2.R

Changes in version 1.11.2:

  • Add a option ‘tabFile’ in the ‘dbCreator’ function for the support of Hisat2 “” in junction construction. As HISAT2 is a successor to both HISAT and TopHat2, we recommend that users switch to ‘tabFile’ from HISAT2 instead of ‘bedFile’ from Tophat2.


Changes in version 1.1.6:

  • Minor bug fixes

Changes in version 1.1.5:

  • PCA plot uses annotation color scheme

  • Rename annotation column implemented

  • log2(1 + x) adjust tool added

  • Calculated annotation revamped

  • Annotate dataset revamped and moved to file

  • Session syncing improved.

  • Sweep adjustment implemented

Changes in version 1.1.3:

  • Option to get vertical GSEA plot

  • Showing heatmap along the GSEA plot

  • Changed filter scheme

  • Better session synching between fronend and backend

Changes in version 1.1.2:

  • Moved to protobuf 3.4 in docker (supports messages up to 2GB)

  • Set exact match to be default

  • Set row profile as the default chart

Changes in version 1.1.1:

  • Fixes in PCA plot


  • Detecting conditions and replicates in GEO data


Changes in version 1.22.0:


  • Update installation instructions in the vignette

Changes in version 1.20.1:


  • Updates to GitHub landing page (


Changes in version 1.7.2 (2018-05-22):


  • The version of the package C50 is now required to be at least 0.1.2, which exports the function.


Changes in version 0.99.37:

New features

  • Added ability to display adjusted p value

Changes in version 0.99.24:

New features

  • Added unit testing for the shiny app.

Changes in version 0.99.15:

New features

  • Can now load .csv and .tsv files.

Changes in version 0.99.14:

Minor improvements and bug fixes

  • Using vapply() instead of sapply() for safer code.


Changes in version 1.99.3:

  • NB function now exported

  • note that version 1.99.3 on GitHub was version 1.1.0 on Bioconductor.

Changes in version 1.99.2:

  • bug fix in fragment generation (last 2 bases of transcript were never sequenced)


Changes in version 1.1.1:

  • Bug fixes for adding missing values in simulations.

Changes in version 1.1.0:

  • The release version.


Changes in version 0.99.7:

  • Initial release of ‘primirTSS’ package


Changes in version 1.21.9:

  • Fix type in vignette header <2018-09-18 Tue>

  • Fix bug in plot method for ThetaRegRes object <2018-09-24 Mon>

Changes in version 1.21.8:

  • Add an fcol argument to plotDist to plot and colour all profiles <2018-08-09 Thu>

Changes in version 1.21.7:

  • Use BiocManager in vignette

  • Fix bug in plot2D: pass … to hexbin <2018-08-02 Thu>

Changes in version 1.21.6:

  • Use BiocManager in installation instructions

Changes in version 1.21.5:

  • Added new section in Bayesian spatial proteomics vignette detailing mcmc output processing <2018-07-07 Sat>

Changes in version 1.21.4:

  • Fix bugs in tagmMcmcPredict, where fcol was ignored <2018-06-05 Tue>

  • Order vignettes by prefixing the files with numbers <2018-06-05 Tue>

Changes in version 1.21.3:

  • New TAGM-MCMC generative model, contributed by Oliver Crook <2018-05-18 Fri>

Changes in version 1.21.2:

  • Version bump for BiocStyle update: Vignette needed to be rebuilt to have bug fixed in BiocStyle footnote rendering.

Changes in version 1.21.1:

  • Fix bug in higlightOnPlot with missing fcol (see #105) <2018-05-03 Thu>

  • New TAGM-MAP generative model, contributed by Oliver Crook <2018-05-18 Fri>

  • New plotEllipse function to visualise and assess TAGM models <2018-05-18 Fri>


Changes in version 1.12.0:


  • normalDB does not need input normal coverage files anymore after creation (so the resulting normalDB.rds file can be moved)

  • base quality filtering can be turned off by setting min.base.quality to 0 or NULL

  • possible to change the POP_AF info field name

  • possible to change POP_AF cutoff to set a high germline prior

  • possible to change min.cosmic.cnt and max.homozygous.loss in PureCN.R

  • set number of cores in PureCN.R (thanks Brad)


  • renamed reptimingbinsize to reptimingwidth in IntervalFile.R, added this feature to preprocessIntervals

  • clarified “targets” vs. “intervals”; whenever something affects both on-target and off-target, it is now called “intervals”. When only targets, e.g. in annotateTargets, “targets” was kept.

  • made gc.gene.file defunct

  • new default for min.cosmic.cnt = 6 (instead of 4)


  • catch various input problems and provide better error messages instead of crashing

  • stranded input BED files do not cause problems anymore

  • fixed a bug when only a single local optimum was tested (happens only when users copy the examples that restrict the search speach to avoid long runtimes)

  • added missing QC flag to predictSomatic VCF annotation


Changes in version 0.99.0:

  • initial version with the following functions implemented: + convertToMSnset + summarizeIntensities + normalizeQuantiles + normalizeScaling + groupScaling + rowScaling + regressIntensity + computeDiffStats + getContrastResults + assignColours + intensityPlot
    • intensityBoxplot + peptideIntensityPlot + pcaPlot + maVolPlot + corrPlot + rliPlot + hierarchicalPlot + plotMeanVar + coveragePlot


Changes in version 1.7.4:

  • Reformated NEWS file

Changes in version 1.7.3:

  • Adapted vignette to BiocManager installation process

Changes in version 1.7.2:

  • Bugfixes: - addCoverage fixed fragment size sd for chromosomes with 1 read - addCoverage fixed missing regions in count_matrix for chromosomes without any reads

Changes in version 1.7.1:

  • Bugfix: addCoverage crashes when there are no reads for chromosome/contig


Changes in version 2.2.0:

  • New functions to remove duplicate edges - deleteDuplicateEdges - deleteSelfLoops

  • New node selection function - selectNodesConnectedBySelectedEdges

  • New visual style management functions - importVisualStyles - deleteVisualStyle - deleteStyleMapping

  • New edge bundling function - bundleEdges

  • New custom graphics options for nodes - setNodeCustomBarChart - setNodeCustomBoxChart - setNodeCustomHeatMapChart - setNodeCustomLineChart - setNodeCustomPieChart - setNodeCustomRingChart - setNodeCustomLinearGradient - setNodeCustomRadialGradient - setNodeCustomPosition - removeNodeCustomGraphics

  • New filter functions - applyFilter - createColumnFilter - createCompositeFilter - createDegreeFilter - getFilterList - exportFilters - importFilters

  • Improved speed on bulk node and edge property bypasses

  • Bug Fixes - selectEdgesConnectingSelectedNodes – set default by.col = ‘name’ - setEdgeLineWidthMapping – fixes input type - getGroupInfo – works without collapsing first - getTableColumns – work with List type columns

  • For Developers - Updated many functions to properly pass the base.url parameter to functions like getNetworkSuid. Please be aware and vigilent about this with future development. - Adopted use of seq_len(). Please be aware and vigilent. - Replaced all but one case of sapply() with vapply().

  • Deprecated - Nothing

  • Defunct - Previously deprecated functions in v2.0 from older 1.x version of the package


Changes in version 1.25.1:

  • add keyType parameter in viewPathway (2018-09-04, Tue)


Changes in version 0.99.0 (2018-07-12):

  • Submitted to Bioconductor


Changes in version 1.7.5:


  • add_metadata() can now download the recount_brain_v2 data.

Changes in version 1.7.4:


  • Fix a NOTE about RefManageR.

Changes in version 1.7.3:


  • Use BiocManager

Changes in version 1.7.2:


  • Fix a unit test.

Changes in version 1.7.1:


  • rse_tx URLs now point to v2 to reflect recent changes by Fu et al.


Changes in version 1.13.2:


  • createRandomRegions ignored the non.overlapping argument. It does work now.

Changes in version 1.13.1:


  • Revamped toGRanges now accepts genome region descriptions as used by UCSC and IGV (“chr9:23000-25000”). It also may take a genome parameter and set the genome information of the GRanges accordingly.


Changes in version 1.15.4:


  • Fix a bug in the order that was reported and fixed by @bounlu at

Changes in version 1.15.3:


  • Fixed an issue with DESeq2Exploration.Rmd that affected both DESeq2Report and edgeReport. This should also fix the recount bioc-release (3.7) and bioc-devel (3.8) branches.

  • Fixed a NAMESPACE issue with rmarkdown::html_document and BiocStyle::html_document

Changes in version 1.15.2:


  • Use BiocManager

Changes in version 1.15.1:


  • Fix namespace issue in relation to BiocStyle::html_document2


Changes in version 1.13.1:

  • plotRegionGeneAssociationGraphs(): par(mfrow) is automatically set according to the length of type.


Changes in version 0.99.25:

  • Update vignette rmd file. <2018-10-26 Thu>

Changes in version 0.99.24:

  • Change description in DESCRIPTION file. <2018-10-24 Tue>

Changes in version 0.99.23:

  • Add show method for ‘RNASeqRParam’ S4 object and revise vignette. <2018-10-16 Tue>


Changes in version 1.99.0:

  • RnBeadsDJ: updated documentation and tooltips

  • deactivated intersample plots (exploratory module) as default option for BS-seq data

  • Roxygen documentation updates

  • Extended methods descriptions in reports (imputation, filtering, differential, …)

  • Miscellaneous bugfixes and performance improvements in RnBeadsDJ, imputation, …

Changes in version 1.13.3:

  • added CNV estimation using the GLAD package to QC module

  • some bugfixes

  • changed ‘gender’ to ‘sex’, affected functions and options are ‘rnb.execute.gender.prediction’ and ‘import.gender.prediction’

Changes in version 1.13.2:

  • added qvalue to suggested packages

Changes in version 1.13.1:

  • Updated LOLA DB download links


Changes in version 2.9.4:

  • Fix unit test <2018-10-06 Sat>

Changes in version 2.9.3:

  • Update news and pkgdown

Changes in version 2.9.2:

  • replace BiocInstaller biocLite mentions with BiocManager

Changes in version 2.9.1:

  • Fix bug ancestors function, reported by Christian Holland (see for details) <2018-06-01 Fri>

Changes in version 2.9.0:

  • Bioconductor devel


Changes in version 1.13.8:


  • minor correction in the documentation

Changes in version 1.13.6:


  • update of package vignette

Changes in version 1.13.4:


  • fixed bug in unit test

Changes in version 1.13.2:


  • predict method: naming of the predicted Y matrix output columns in case of PLS modeling of multiple responses


  • ropls.Rproj file added for package management with RStudio


Changes in version 1.17.2:

  • Update NEWS and pkgdown site

Changes in version 1.17.1:

  • replace BiocInstaller biocLite mentions with BiocManager

Changes in version 1.17.0:

  • New version for Bioconductor devel


Changes in version 1.33:


  • (v 1.33.4, 1.33.7) scanBamFlag() gains isSupplementaryAlignment support.


  • (v 1.33.1) Do not try to grow NULL (not-yet-encountered) tags ( ; Robert Bradley)

  • (v 1.33.5) Check for corrupt index ( ; kjohnsen)


Changes in version 1.32.0:

  • New function flattenGTF() that merges overlapping features into a single interval.

  • New parameter for align() and subjunc(): sortReadsByCoordinates.

  • New parameters for featureCounts(): readShiftType, readShiftSize and additionalAttributes.

  • Specify strand protocol for each library individually in featureCounts().

  • Much improved speed of align() and subjunc().

  • align() and subjunc() return mapping statistics.

  • Default setting of buildindex() is changed to building a one-block full index.


Changes in version 2.6.0:

  • Make available GSEA-2T and aREA-3T algorithms for single-sample analysis.


Changes in version 1.6.0:

  • Improved workflow, integration with derivative packages (RTN / RTNsurvival).


Changes in version 0.20.0


  • rbind() now supports DataFrame objects with the same column names but in different order, even when some of the column names are duplicated. How rbind() re-aligns the columns of the various objects to bind with those of the first object is consistent with what does.

  • Add isSequence() low-level helper.

  • Add ‘nodup’ argument to selectHits().


  • The rownames of a DataFrame are no more required to be unique.

  • Change ‘use.names’ default from FALSE to TRUE in mcols() getter.

  • Coercion to DataFrame now always propagates the names.

  • Rename low-level generic concatenateObjects() -> bindROWS().

  • replaceROWS() now dispatches on ‘x’ and ‘i’ instead of ‘x’ only.

  • Speedup row subsetting of DataFrame with many columns.


  • phead(), ptail(), and strsplitAsListOfIntegerVectors() are now defunct (after being deprecated in BioC 3.7).


  • Fix window() on a DataFrame with data.frame columns.

  • 2 fixes to “rbind” method for DataFrame objects: + It now properly handles DataFrame objects with duplicated colnames. Note that the new behavior is consistent with + It now properly handles DataFrame objects with columns that are 1D arrays.

  • Fix showAsCell() on nested data-frame-like objects.

  • 2 fixes to “” method for DataFrame objects: + It now works if the DataFrame object contains nested data-frame-like objects or other complicated S4 objects (as long as these complicated objects in turn support + It now handles ‘stringsAsFactors’ argument properly. Originally reported here:


Changes in version 1.10.0:

  • Fixes to all violin plots to ensure scatter matches up with violin outlines.

  • Rectangle categorical/categorical plots collapse to mirrored bar plots when either factor contains only one level.

  • Removed scater_gui(), downsampleCounts(), read10xResults(), normalizeExprs().

  • Simplified plotRLE() to avoid the need for internal faceting.

  • Added option for row subsetting in librarySizeFactors().

  • Ensured calcAverage() with subset_row= behaves as if the matrix was subsetted prior to the function call. Added support for parallelization.

  • Ensured calculateCPM() with subset_row= behaves as if the matrix was subsetted prior to the function call.

  • Added support for parallelization in nexprs().

  • Added readSparseCounts() for creating a sparse matrix from a dense array on file.

  • Added normalizeCounts() for easy division of matrix columns by the size factors. Modified to throw error upon encountering negative, NA or zero size factors.

  • Added preserve_zeroes= option to normalizeSCE() for preserving sparsity with non-unity pseudo-counts.

  • Added runUMAP() and plotUMAP() to use the UMAP dimensionality reduction method.

  • Added plotExplanatoryPCs() and getExplanatoryPCs() to correlate PCs with known factors. Deprecated findImportantPCs().

  • Added getVarianceExplained() to get the variance in gene expression explained by known factors.

  • Removed runKallisto() and runSalmon().

  • Switched readTxResults() to use tximport. Switched readSalmonResults() and readKallistoResults() to use readTxResults().

  • Removed obsolete fields in calculateQCMetrics(). Moved processing into C++ for a single-pass algorithm. Supported parallelization across cells for QC computations.

  • Added sumCountsAcrossFeatures() to sum counts across multiple redundant features. Deprecated summariseExprsAcrossFeatures().

  • All plotting functions can now access internal fields by using a character vector with NA as the first element.

  • Returned threshold values in the attributes of the output from isOutlier().

  • Deprecated the ticks in plotReducedDim().


Changes in version 0.99.1:

  • Modify description part in DESCRIPTION file.

  • Change seq_len(length(x)) to seq_along(x) in sageTestNew.R function.


Changes in version 1.1.7:


  • methylationDist function produces more interpretable mean methylation values

  • In addition to the report file QC_Summary text file is generated. Also mbias table and downsample table are stored as text file

  • Added “all” option in functions that utilizes subsampling such that given “all” option certain function would be applied to all the CpGs without any subsample or offset


Changes in version 1.3.8:

  • fix a minor bug in cell barcode demultiplexing

Changes in version 1.3.6:

  • support multiple bam file for the same sample pooling as input for exon mapping

Changes in version 1.3.5:

  • bug fix

Changes in version 1.3.4:

  • put distance_to_end back.

Changes in version 1.3.2:

  • Added gzipped output for sc_trim_barcode(), if output filename ends with .gz then gzipped output will be produced.

  • Added get_read_str() function for getting common read structures.

Changes in version 1.3.1:

  • updated the sc_exon_mappping function so it can accept multiple bam files now, together with a list of cell id or cell barcode.


Changes in version 1.10.0:

  • Removed selectorPlot(), exploreData() functions in favour of iSEE.

  • Fixed underflow problem in mnnCorrect() when dealing with the Gaussian kernel. Dropped the default sigma= in mnnCorrect() for better default performance.

  • Supported parallelized block-wise processing in quickCluster(). Deprecated max.size= in favour of max.cluster.size= in computeSumFactors(). Deprecated get.ranks= in favour of scaledColRanks().

  • Added max.cluster.size= argument to computeSumFactors(). Supported parallelized cluster-wise processing. Increased all pool sizes to avoid rare failures if number of cells is a multiple of 5. Minor improvement to how mean filtering is done for rescaling across clusters in computeSumFactors(). Throw errors upon min.mean=NULL, which used to be valid. Switched positive=TRUE behaviour to use cleanSizeFactors().

  • Added simpleSumFactors() as a simplified alternative to quickCluster() and computeSumFactors().

  • Added the scaledColRanks() function for computing scaled and centred column ranks.

  • Supported parallelized gene-wise processing in trendVar() and decomposeVar(). Support direct use of a factor in design= for efficiency.

  • Added doubletCluster() to detect clusters that consist of doublets of other clusters.

  • Added doubletCells() to detect cells that are doublets of other cells via simulations.

  • Deprecated rand.seed= in buildSNNGraph() in favour of explicit set.seed() call. Added type= argument for weighting edges based on the number of shared neighbors.

  • Deprecated rand.seed= in buildKNNGraph().

  • Added multiBlockNorm() function for spike-abundance-preserving normalization prior to multi-block variance modelling.

  • Added multiBatchNorm() function for consistent downscaling across batches prior to batch correction.

  • Added cleanSizeFactors() to coerce non-positive size factors to positive values based on number of detected genes.

  • Added the fastMNN() function to provide a faster, more stable alternative for MNN correction.

  • Added BPPARAM= option for parallelized execution in makeTechTrend(). Added approx.npts= option for interpolation-based approximation for many cells.

  • Added pairwiseTTests() for direct calculation of pairwise t-statistics between groups.

  • Added pairwiseWilcox() for direct calculation of pairwise Wilcoxon rank sum tests between groups.

  • Added combineMarkers() to consolidate arbitrary pairwise comparisons into a marker list.

  • Bugfixes to uses of block=, lfc= and design= arguments in findMarkers(). Refactored to use pairwiseTTests() and combineMarkers() internally. Added BPPARAM= option for parallelized execution.

  • Refactored overlapExprs() to sort by p-value based on pairwiseWilcox() and combineMarkers(). Removed design= argument as it is not compatible with p-value calculations.

  • Bugfixes to the use of Stouffer’s Z method in combineVar().

  • Added combinePValues() as a centralized internal function to combine p-values.


Changes in version 1.1.2:

  • update NEWS file.

Changes in version 1.1.1:

  • allow adjustment of covariates;

  • update ‘SDA’ with additional arguments passed to ‘qvalue’.


Changes in version 1.21.1-1.21.7:


  • avoid duplicated meta-information lines in seqVCF2GDS() and seqVCF_Header()

  • require >= R_v3.5.0, since reading from connections in text mode is buffered

  • seqDigest() requires the digest package

  • optimization in reading genotypes from a subset of samples (according to gdsfmt_1.17.5)


  • seqSNP2GDS() imports dosage GDS files

  • seqVCF_Header() allows a BCF file as an input

  • a new function seqRecompress()

  • a new function seqCheck() for checking the data integrity of a SeqArray GDS file

  • seqGDS2SNP() exports dosage GDS files


  • seqVCF2GDS() and seqVCF_Header() are able to import site-only VCF files (i.e., VCF with no sample)

  • fix seqVCF2GDS() and seqBCF2GDS() since reading from connections in text mode is buffered for R >= v3.5.0

Changes in version 1.20.1:


  • seqExport() fails to export haploid data (e.g., Y chromosome)

  • seqVCF2GDS() fails to convert INFO variables when Number=”R”


Changes in version 1.4.0:


  • Add convenience functions for creating and reading multiple SNV profiles

  • Add functionality for reading general COSMIC mutational data, not just cell line mutational data


  • Fix an issue when reading COSMIC data due to new GRanges functionality


  • Update the citation info with the now-published seqCAT-specific article


Changes in version 1.0.0:

  • First submission of SeSAMe package.


Changes in version 1.7.1:

  • optimization of genCountMatrixFromVcf function


Changes in version 1.13.1:

  • fix compatibility issues with new ggplot package [2018-08-02 Wed]


Changes in version 0.99.9:

  • put return statement in code at the end.

  • instead of writing at each line, you paste output lines in a single paste call and then use a single write call.

  • use a package BiocManager instead of biocLite in the vignettes.

  • remove a few eval=FALSE sections in vignette to ensure vignette to be evaluated.

Changes in version 0.99.8:

  • Modify vignette output to BiocStyle .

  • Add some information in README file.

Changes in version 0.99.6:

  • Adjust the code format to follow the coding style.

  • Generate NEWS file in .Rd form.

  • Add some information in, vignettes and DESCRIPTION file to make the package SIMD be more understandable.

Changes in version 0.99.5:

  • Modify the ‘TIMEOUT’ happened in R biocheck.

Changes in version 0.99.4:

  • Modify some problems in R biocheck.

Changes in version 0.99.3:

  • Modify some problems in R biocheck.

  • Recompile .Rd by roxygen2 package in R.

Changes in version 0.99.2:

  • Modify some problems in R biocheck.

  • Change the NEWS format.

Changes in version 0.99.1:

  • Modify the problem in R check.

  • To get the vignettes by R Markdown instead of by Sweave.

  • Add in package.


Changes in version 1.7.3 (2018-10-13):

  • Removed CIMLR implementation.


Changes in version 1.15.1:

  • Updated getTrueModel, zmatrix, simTime to include additional covariates as predictors

  • Simplified examples


Changes in version 1.4.0:

  • Allow … arguments to be passed to rowData() and colData().

  • Added weights() methods for getting/setting observational weights.

  • Added reducedDimNames<- method to set the names of reduced dimension slots.

  • Added withDimnames= argument to reducedDim() and reducedDims().

  • Exported getters and setters for internal metadata fields.

  • Added developer instructions for making use of internal metadata fields.


Changes in version 1.1.26 (2018-10-23):

  • New UI design for the Differential Expression tab.

  • New UI design for the Data Summary & Filtering tab.

  • Support for additional assay modification including log transforming any assay and renaming assays.

  • New function visPlot for creating scatterplots, boxplots, heatmaps, and barplots for custom gene sets.

  • The Downsample tab now works on a generic counts matrix

  • You can upload a SCtkExperiment object or a SingleCellExperiment object saved in an RDS file on the Upload tab.

  • Differential Expression results can now be saved in the rowData of the object and loaded for later analysis.

  • Improved ability to save a biomarker based on user options.

  • The Differential Expression plot is not automatically created, for more user control with large datasets.

Changes in version 1.1.3:

  • Improvements to plotting, change text size and hide labels in gsva plots.

  • MAST violin and linear model plots are now more square when plotting less than 49 facets.

  • Changed y axis label in plotBatchVariance to “Percent Explained Variation”

Changes in version 1.1.2:

  • Ability to hide version number in the SCTK GUI.

Changes in version 1.1.1:

  • Fixed a bug that would cause the diffex color bar to not display when special characters were in the annotation.


Changes in version 0.99.0:


  • Initial submission. Everything is new and shiny.


Changes in version 1.15.1-1.15.5:

  • a new option ‘useMatrix’ to allow for the packed symmetric matrix using the Matrix package in snpgdsIBDMoM(), snpgdsIBDKING() and snpgdsIBS()

  • fix a bug of missing sample and SNP IDs in the output of snpgdsIndInb()

  • new option ‘start.pos’ in snpgdsLDpruning()

  • new methods in snpgdsIndInb(): gcta1, gcta2, gcta3; progress information is shown during running the function

  • snpgdsCombineGeno() supports dosages


Changes in version 1.1.4:

  • Move NMF to Depends section

Changes in version 1.1.3:

  • Issue with the basis function solved


Changes in version 2.0:


  • New GUI o Mouse Hover for help information o .log file

  • New Signal correction o QC-RFSC methods for metabolomics and proteomics data

  • New feature slection o Random Forest and the Permutation based variable importance measures o new MDSplot for Random Forest o P-value based importance plot

  • New data preprocessing o PQN/SUM/none normalization o center/none Scaling method


Changes in version 0.99.16:

  • Submitted version to Bioconductor


Changes in version 1.12.0:


  • The package has a new vignette “Extending the SummarizedExperiment class” by Aaron Lun intended for developers. It documents in great details the process of implementing a SummarizedExperiment extension (a.k.a. subclass).


  • rowData() gains use.names=TRUE argument; prior behavior was to use.names=FALSE. rowData() by default fails when rownames() contains NAs.


  • Better error handling in SummarizedExperiment() constructor. SummarizedExperiment() now prints an informative error message when the supplied assays have insane rownames or colnames. This addresses


Changes in version 1.11.7:


  • avoid sorting when adding gene symbols in add_gene_symbol

Changes in version 1.11.6:


  • fix manual page and function in convert_protein_ids to copy non-converted IDs

Changes in version 1.11.5:


  • move from bioclite to BiocManager

Changes in version 1.11.4:


  • fix manual page to convert_protein_ids

Changes in version 1.11.3:


  • updates to convert_protein_ids, see that convert4aLFQ outputs character vectors

Changes in version 1.11.2:


  • add functions convert_protein_ids, load_mart, add_genesymbol

Changes in version 1.11.1:


  • remove links from manual page SWATH2stats-package

Changes in version 1.11.0:


  • SWATH2stats in BioC 3.8 development release


Changes in version 2.5.2:

  • Use BiocManager::install [2018-07-16]. # Synapter 2.3


Changes in version 1.38.0:


  • New function checkRimLim to vizualise a retention index markers before the actual time correction. It can be useful to fix the search limits.

  • Peak detection method (NetCDFPeakFinding) has the option to use a gaussian smoothing in addition to usual moving average.

  • Detects if CDF files are not found during sample description import. In addition, search for column names matching a pattern if the expected names are not found.

  • Add support for a custom CDF file for faster data retrieval.


  • The parameter massRange (m/z mass range) which used to be needed in some functions is deprected. It was used mostly as a hint and usually detected automatically. If it is passed, there would be no effect.


  • Big refactor of C code to eliminate duplicated code and to separate what is R-C code (ie, SEXP structs) out of the C code that actually does something.

  • General R code refactoring and housekeeping.


Changes in version 1.21.3:

  • fixed bug (order of outputs from devel version of baySeq cannot be sorted) in ‘.testByBayseq’.

  • disabled ‘samseq’ option, since samr package has been removed from CRAN.

  • change design matrix used in DESeq2


Changes in version 1.1.1:

New Features:

  • The function GeneID2entrez now suports translation from mouse ENSEMBL gene IDs and MGI symbols to mouse Entrez gene IDs

  • 76 new ChIP-Seq experiments added to the database


Changes in version 099.1:


  • changed function behvaiour in the whole package from call-by-ref to call-by value. Adjusted accordingly all examples and the vignette.


  • depends now on ProtGenerics from which it uses ‘mz’

  • exchanged various print() with message()


Changes in version 1.3.6:

  • Add Pavel’s and Ole’s ORCID to DESCRIPTION [2018-10-23].

Changes in version 1.3.5:

  • Fix format of roxygen links to foreign packages to avoid link warning in R CMD check [2018-10-10].

Changes in version 1.3.4:

  • Add inst/CITATION file [2018-09-26].

Changes in version 1.3.3:

  • Revert commit c6e8dfd: “Adapt to MSnbase 2.7.2 with internal fragments; see #82 [2018-06-03].”

Changes in version 1.3.2:

  • Use BiocManager::install [2018-07-16].

Changes in version 1.3.1:

  • Adapt to MSnbase 2.7.2 with internal fragments; see #82 [2018-06-03].

  • Fix FragmentViews start/end/width and labels for internal fragments [2018-06-03].

  • Fix as(tds, "MSnSet") unit test [2018-07-06].

  • Use elementMetadata(..., use.names=FALSE) in combine,FragmentViews,FragmentViews-method to avoid duplicated rownames in elementMetadata slot [2018-07-06].

Changes in version 1.3.0:

  • New version for Bioc 3.8 (devel) # topdownr 1.2


Changes in version 1.17.8:

  • fix the bug in figure captions of vignette.

Changes in version 1.17.7:

  • allow ylim of tracks be not fixed from 0.

Changes in version 1.17.6:

  • fix a issue of circle in lollipop plot.

Changes in version 1.17.4:

  • add flag type in lollipop plot.

Changes in version 1.17.3:

  • adjust plot position for dandelion.plot.

Changes in version 1.17.2:

  • add Yscales for dandelion.plot.

Changes in version 1.17.1:

  • add smooth function for tracks.


Changes in version 1.3.6:

  • Slot genesInTerm added to the Transcriptogram class.

  • Argument boundaryConditions from differentiallyExpressed(): default changed from FALSE to TRUE.

  • Argument onlyGenesInDE from clusterVisualization(): default changed from TRUE to FALSE.

  • Argument onlyGenesInDE from clusterEnrichment(): default changed from TRUE to FALSE.

  • Argument colors added to the differentiallyExpressed() method.

  • Argument colors added to the clusterVisualization() method.

  • Argument colors added to the enrichmentPlot() method.

  • Argument alpha added to the enrichmentPlot() method.

Changes in version 1.3.4:

  • Argument universe from clusterEnrichment(): default changed from “all the proteins present in the transcriptogramS2 slot” to “all the proteins present in the ordering slot”.

Changes in version 1.3.3:

  • Changes on the clusterEnrichment() method return.

  • Slots Protein2GO, and Terms added to the Transcriptogram class.

  • New methods: enrichmentPlot() and Terms().

Changes in version 1.3.1:

  • Argument boundaryConditions added to the differentiallyExpressed() method.

  • Slots Protein2Symbol, clusters, and pbc added to the Transcriptogram class.

  • Argument onlyGenesInDE added to the clusterVisualization() method.

  • Argument onlyGenesInDE added to the clusterEnrichment() method.


Changes in version 0.99.0:

  • initial release


Changes in version 1.1.9 (2018-10-24):

  • moved some functionality to tRNA package

  • added dependency for tRNA package

Changes in version 1.1.1 (2018-08-16):

  • bugfix for recognizing pseudogene annotation


Changes in version 0.0.16:

  • Added examples to all man pages.


Changes in version 1.9.11:

  • Exporting simple internal function makeCountsFromAbundance().

Changes in version 1.9.10:

  • Added ‘infRepStat’ argument which offers re-compution of counts and abundances using a function applied to the inferential replicates, e.g. matrixStats::rowMedian for using the median of posterior samples as the point estimate provided in “counts” and “abundance”. If ‘countsFromAbundance’ is specified, this will compute counts a second time from the re-computed abundances.

Changes in version 1.9.9:

  • Adding support for gene-level summarization of inferential replicates. This takes place by perform row summarization on the inferential replicate (counts) in the same manner as the original counts (and optionally computing the variance).

Changes in version 1.9.6:

  • Added new countsFromAbundance method: “dtuScaledTPM”. This is designed for DTU analysis and to be used with txOut=TRUE. It provides counts that are scaled, with a gene, by the median transcript length among isoforms, then later by the sample’s sequencing depth, as in the other two methods. The transcript lengths are calculated by first taking the average across samples. With this new method, all the abundances within a gene across all samples are scaled up by the same length, preserving isoform proportions calculated from the counts.

Changes in version 1.9.4:

  • Made a change to summarizeToGene() that will now provide different output with a warning to alert the user. The case is: if tximport() is run with countsFromAbundance=”scaledTPM” or “lengthScaledTPM” and txOut=TRUE, followed by summarizeToGene() with countsFromAbundance=”no”. This is a problematic series of calls, and previously it was ignoring the fact that the incoming counts are not original counts. Now, summarizeToGene() will throw a warning and override countsFromAbundance=”no” to instead set it to the value that was used when tximport was originally run, either “scaledTPM” or “lengthScaledTPM”.

Changes in version 1.9.1:

  • Fixed edgeR example code in vignette to use scaleOffset after recommendation from Aaron Lun (2018-05-25).


Changes in version 0.99.0:

  • Pre-Bioconductor submission


Changes in version 2.1.4 (2018-10-10):

Bioconductor compliance

  • Minor bugfixes regarding the removal of CCLs

Changes in version 2.1.3 (2018-10-03):

Bioconductor compliance

  • Minor bugfixes regarding the removal of CCLs and reference libraries


Changes in version 1.11.13:

  • Fix multithreading issue

Changes in version 1.11.11:

  • dream can handle multiple contrasts at the same time

Changes in version 1.11.10:

  • fix typos in dream vignette

Changes in version 1.11.8:

  • Check and stop() if response variable has variance of 0 - in dream(), fitExtractVarPartModel(), and fitVarPartModel()

  • add standardized_t_stat() implicitly in eBayes() using MArrayLM2 class - this transforms moderated t-statistics to have same degrees of freedom

Changes in version 1.11.7:

  • Simplify object return by dream to be more more similar to lmFit - now returns MArrayLM instead of MArrayLMM_lmer

  • if a fixed effects formula is specified (i.e. not random terms) - dream call lmFit in the backend - getContrast() works seamlessly

  • dream() now returns gene annotation if passed to function

Changes in version 1.11.6:

  • add error checing for L in dream

  • fix typoes in dream vignette

  • fix typoes in theory_practice_random_effects.Rnw

Changes in version 1.11.5:

  • Add dream function for differential expression for repeated measures with a linear mixed model

Changes in version 1.11.2:

  • Add warnings to canCorPairs for colinear terms

Changes in version 1.11.1:

  • Add vignette: theory_practice_random_effects.Rnw


Changes in version 1.28.0:


  • Update package to support VCF format version 4.3 - SAMPLE field lines can now have key ‘SAMPLE’ or ‘META’. To avoid a name clash, the existing ‘META’ DataFrame has been split by row into separate DataFrames. The ‘meta(VCFHeader)’ getter now returns one DataFrame per unique key in the header. - PEDIGREE header line now begins with ‘ID’

  • Add vcfFields method for character, VCFHeader, VcfFile and VCF to return all available vcf fields in CharacterList().

  • Add support for single breakend notation (thanks d-cameron)


  • .formatInfo() now return a column with all ‘NA’ for a missing value instead of dropping the column.


Changes in version 3.3.6:

  • Add type = “polygon” to highlightChromPeaks allowing to fill the actual signal area of identified chromatographic peaks.

Changes in version 3.3.5:

  • Performance enhancement of the chromPeakSpectra and featureSpectra functions.

Changes in version 3.3.4:

  • Add featureChromatograms to extract ion chromatograms for each feature.

  • Add hasFilledChromPeaks function.

  • Add argument skipFilled to the featureSummary function.

Changes in version 3.3.3:

  • Add chromPeakSpectra and featureSpectra functions to extract MS2 spectra for chromatographic peaks and features, respectively (issue #321).

  • Fix profMat to handle also data files with empty spectra (issue #312).

  • Add argument ylim to plotAdjustedRtime (issue #314).

  • Add imputeRowMin and imputeRowMinRand, two simple missing value imputation helper functions.

  • Fix additional problem mentioned in issue #301 with obiwarp retention time correction if some spectra have m/z values of NA.

  • Fix issue #300 avoiding chromatographic peaks with rtmin > rtmax.

  • Fixes for issues #291, #296.

  • Add parameter ‘missing’ to diffreport allowing to replace NA with arbitrary numbers.

  • Add exportMetaboAnalyst function to export the feature matrix in MetaboAnalyst format.

  • Add parameter missing to featureValues allowing to specify how to handle/ report missing values.

  • The chromPeaks matrix has now rownames to uniquely identify chromatographic peaks in an experiment. Chromatographic peak IDs start with “CP” followed by a number.

Changes in version 3.3.2:

  • Add writeMSData method for XCMSnExp allowing to write mzML/mzXML files with adjusted retention times (issue #294).

  • Fix profEIC call for single-scan-peak (pull request #287 from @trljcl).

  • Fix centWave avoiding that the same peak is reported multiple times if fitgauss = TRUE is used (issue #284).

  • featureSummary reports also RSD (relative standard deviations) of features across samples (issue #286).

  • Add parameters fixedMz and fixedRt to FillChromPeaksParam that allow to increase the features’ m/z and rt widths by a constant factor.

  • Add option “sum” to featureValues’ method parameter allowing to sum the intensities of peaks that are assigned to the same feature in a file/sample.

Changes in version 3.3.1:

  • Add overlappingFeatures function to identify overlapping or close features.

  • Add support for type = “apex_within” for featureDefinitions.

  • Fix a bug in fillChromPeaks that would return the integrated signal being Inf.

  • Fix for issue #267: error in fillChromPeaks when the retention time of the peaks are outside of the retention time range of certain files.

  • New featureSummary function to calculate basic feature summaries (number of samples in which peaks were found etc).

  • Parameter ‘type’ added to plotChromPeakDensity and ‘whichPeaks’ to highlightChromPeaks. Both parameters are passed to the ‘type’ argument of chromPeaks.

  • Parameter ‘type’ in chromPeaks gets additional option “apex_within” to return chromatographic peaks that have their apex within the defined rt and/or m/z range.

  • Add functions rla and rowRla to calculate RLA (relative log abundances).

  • Add peaksWithMatchedFilter to perform peak detection in chromatographic (MRM/SRM) data (issues #277 and #278).

  • Add peaksWithCentWave to perform centWave peak detection in chromatographic (MRM/SRM) data (issue #279).

  • Add findChromPeaks,Chromatogram methods for CentWaveParam and MatchedFilterParam (issue #280).


Changes in version 1.0.0:


  • No changes


  • No changes classified as ‘bug fixes’ (package under active development)


Changes in version 1.41:

  • update NEWS file


Changes in version 1.3.1 (2018-05-09):

  • New zinbsurf function implements approximate method for large matrices.

  • New option which_genes in zinbwave to specify which genes to use to compute W.

NEWS from new and existing Data Experiment Packages


Changes in version 0.99.0 (2018-08-05):

  • Submitted to Bioconductor


Changes in version 1.0:

  • Package release


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 0.1.0:

  • Initial version of the package


Changes in version 0.99.37 (2018-10-25):

  • Made the following significant changes o Initial release to Bioconductor o Updated manuscript reference

Changes in version 0.99.36 (2018-03-24):

  • Submitted to Bioconductor

  • Added NEWS file


Changes in version 0.99.8 (2018-06-30):

  • Changed: GO.rda to

  • Added: vignettes

Changes in version 0.99.1 (2018-06-04):

  • Added: GO.rda and Fantom5.TF.rda


Changes in version 1.0.1:

  • Package submission


Changes in version 1.19.4:

  • New yeast spatial proteome dataset <2018-08-14 Tue>

Changes in version 1.19.3:

  • New synechocystis spatial proteome <2018-07-26 Thu>

Changes in version 1.19.2:

  • Fix typo in beltran2016 man page <2018-07-24 Tue>

  • Added LOPIT-DC and hyperLOPIT U2OS data <2018-07-25 Wed>

Changes in version 1.19.1:

  • Adding hyperLOPIT TAGM results <2018-05-21 Mon>

Changes in version 1.19.0:

  • New Bioconductor devel version


Changes in version 2016-04-21:

  • Initial release for Bioconductor


Changes in version 0.99.0:

  • Initial commit with data from the qPLEX-RIME and Full proteome TMT.


Changes in version 1.19.3:

  • Use BiocManager

  • Fix typo in rmd

Changes in version 1.19.0:

  • New Bioconductor devel version


Changes in version 1.0.0:

  • First submission of sesameData package.


Changes in version 0.99.0:

  • Initial version of the package


Changes in version 0.99.3:


  • This is a data package containing Whole Genome Bisulfite Sequencing (WGBS) data from TCGA.

NEWS from new and existing Workflows


Changes in version 1.99.6:

  • some minor fixes to RLE section

  • minor text edits as suggested by James McDonald at F1000

  • modified to code chunk that checks for latex compilation

Changes in version 1.99.2:

  • changed installation instructions to BiocManager

Changes in version 0.99.0:

  • new submission to Bioc in June 18


Changes in version 1.3.1:


  • Use BiocManager

Deprecated and Defunct Packages

Seven software packages were removed from this release (after being deprecated in Bioc 3.7): ontoCat, spliceR, OperaMate, DASC, PAnnBuilder, phenoDist, BrowserVizDemo.

Thirteen software are deprecated in this release and will be removed in Bioc 3.9: BiocInstaller, GoogleGenomics, IrisSpatialFeatures, facopy, gaucho, nudge, RamiGO, mQTL.NMR, cytofkit, pbcmc, GeneSelector, ampliQueso, prot2D.

Three experimental data packages were removed in this release (after being deprecated in BioC 3.7): RnaSeqTutorial, cheung2010, MEALData.

Two experimental data packages are deprecated in this release and will be removed in Bioc 3.9: iontreeData, MSBdata.