This package provides functions and routines useful in the analysis of somatic signatures (cf. L. Alexandrov et al., Nature 2013). In particular, functions to perform a signature analysis with known signatures and a signature analysis on stratified mutational catalogue (SMC) are provided.

The purpose of this GO.db annotation package is to provide detailed information about the latest version of the Gene Ontologies.

This package provides Affymetrix HG-U133_Plus_2 array annotation data (chip hgu133plus2) assembled using data from public repositories.

This package provides a number of utility functions for handling single-cell RNA-seq data from droplet technologies such as 10X Genomics. This includes data loading from count matrices or molecule information files, identification of cells from empty droplets, removal of barcode-swapped pseudo-cells, and downsampling of the count matrix.

This package provides functions to annotate microarrays, find orthologs, and integrate heterogeneous gene expression profiles using annotation and other molecular biology information available as flat file database (plain text files).

This package provides a collection of tools for analyzing and visualizing bisulfite sequencing data.

Gene Set Variation Analysis (GSVA) is a non-parametric, unsupervised method for estimating variation of gene set enrichment through the samples of a expression data set. GSVA performs a change in coordinate systems, transforming the data from a gene by sample matrix to a gene-set by sample matrix, thereby allowing the evaluation of pathway enrichment for each sample. This new matrix of GSVA enrichment scores facilitates applying standard analytical methods like functional enrichment, survival analysis, clustering, CNV-pathway analysis or cross-tissue pathway analysis, in a pathway-centric manner.

R-dsb improves protein expression analysis in droplet-based single-cell studies. The package specifically addresses noise in raw protein UMI counts from methods like CITE-seq. It identifies and removes two main sources of noise—protein-specific noise from unbound antibodies and droplet/cell-specific noise. The package is applicable to various methods, including CITE-seq, REAP-seq, ASAP-seq, TEA-seq, and Mission Bioplatform data. Check the vignette for tutorials on integrating dsb with Seurat and Bioconductor, and using dsb in Python.

This R package provides tools for handling genomic interaction data, such as ChIA-PET/Hi-C, annotating genomic features with interaction information and producing various plots and statistics.

This package provides full genome sequences for Mus musculus (Mouse) as provided by UCSC (mm9, July 2007) and stored in Biostrings objects.

This package provides tools for differential expression analysis at both gene and isoform level using RNA-seq data

This package provides a parser for mzIdentML files implemented using the XML package. The parser tries to be general and able to handle all types of mzIdentML files with the drawback of having less pretty output than a vendor specific parser.

This package provides a toolset for deciphering and managing biological sequences.

This package provides robust model-based clustering using a t-mixture model with Box-Cox transformation.

This package provides a flexible method for fitting regression models that can be used to find genes that are differentially expressed along one or multiple lineages in a trajectory. Based on the fitted models, it uses a variety of tests suited to answer different questions of interest, e.g. the discovery of genes for which expression is associated with pseudotime, or which are differentially expressed (in a specific region) along the trajectory. It fits a negative binomial generalized additive model (GAM) for each gene, and performs inference on the parameters of the GAM.

This package provides SNP locations and alleles for Homo sapiens extracted from NCBI dbSNP Build 144. The source data files used for this package were created by NCBI on May 29-30, 2015, and contain SNPs mapped to reference genome GRCh37.p13. Note that the GRCh37.p13 genome is a patched version of GRCh37. However the patch doesn't alter chromosomes 1-22, X, Y, MT. GRCh37 itself is the same as the hg19 genome from UCSC *except* for the mitochondrion chromosome. Therefore, the SNPs in this package can be injected in BSgenome.Hsapiens.UCSC.hg19 and they will land at the correct position but this injection will exclude chrM (i.e. nothing will be injected in that sequence).

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

This is the classification package for the automated analysis of Affymetrix arrays.

This package provides HDF5 storage based methods and functions for manipulation of flow cytometry data.

This package provides publicly available data from The Cancer Genome Atlas (TCGA) as MultiAssayExperiment objects. MultiAssayExperiment integrates multiple assays (e.g., RNA-seq, copy number, mutation, microRNA, protein, and others) with clinical / pathological data. It also links assay barcodes with patient identifiers, enabling harmonized subsetting of rows (features) and columns (patients / samples) across the entire multi-'omics experiment.

This package implements different performance measures for classification and ranking tasks. Area under curve (AUC), precision at a given recall, F-score for single and multiple classes are available.

This package provides a GUI for analysis of Affymetrix microarray gene expression data using the affy and limma packages.

This package contains gene-level counts for a collection of public scRNA-seq datasets, provided as SingleCellExperiment objects with cell- and gene-level metadata.

This package offers the possibility to access the ArrayExpress repository at EBI (European Bioinformatics Institute) and build Bioconductor data structures: ExpressionSet, AffyBatch, NChannelSet.