The PSMatch package helps proteomics practitioners to load, handle and manage peptide spectrum matches. It provides functions to model peptide-protein relations as adjacency matrices and connected components, visualise these as graphs and make informed decision about shared peptide filtering. The package also provides functions to calculate and visualise MS2 fragment ions.

This package provides a set of functions to create and interact with dynamic documents and vignettes.

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.

This package provides full genome sequences for Homo sapiens (Human) as provided by UCSC (hg19, Feb. 2009) and stored in Biostrings objects. The sequences are the same as in BSgenome.Hsapiens.UCSC.hg19, except that each of them has the 4 following masks on top: (1) the mask of assembly gaps (AGAPS mask), (2) the mask of intra-contig ambiguities (AMB mask), (3) the mask of repeats from RepeatMasker (RM mask), and (4) the mask of repeats from Tandem Repeats Finder (TRF mask). Only the AGAPS and AMB masks are "active" by default.

This package implements algorithms for calculating microarray enrichment (ACME), and it is a set of tools for analysing tiling array of combined chromatin immunoprecipitation with DNA microarray (ChIP/chip), DNAse hypersensitivity, or other experiments that result in regions of the genome showing enrichment. It does not rely on a specific array technology (although the array should be a tiling array), is very general (can be applied in experiments resulting in regions of enrichment), and is very insensitive to array noise or normalization methods. It is also very fast and can be applied on whole-genome tiling array experiments quite easily with enough memory.

This package provides a test harness for bsseq loading of Biscuit output, summarization of WGBS data over defined regions and in mappable samples, with or without imputation, dropping of mostly-NA rows, age estimates, etc.

This package offers functionality for taking methtuple or Bismark outputs to calculate ASM scores and compute DAMEs regions. It also offers nice visualization of methyl-circle plots.

Monocle 3 performs clustering, differential expression and trajectory analysis for single-cell expression experiments. It orders individual cells according to progress through a biological process, without knowing ahead of time which genes define progress through that process. Monocle 3 also performs differential expression analysis, clustering, visualization, and other useful tasks on single-cell expression data. It is designed to work with RNA-Seq data, but could be used with other types as well.

This package provides the full genome sequences for Bos taurus (UCSC version bosTau8).

This is a package for detection of differentially bound regions in ChIP-seq data with sliding windows, with methods for normalization and proper FDR control.

This package offers tools to create DNA barcode sets capable of correcting insertion, deletion, and substitution errors. Existing barcodes can be analyzed regarding their minimal, maximal and average distances between barcodes. Finally, reads that start with a (possibly mutated) barcode can be demultiplexed, i.e. assigned to their original reference barcode.

This package provides high performance functions for row and column operations on sparse matrices. Currently, the optimizations are limited to data in the column sparse format.

This package provides a package for the annotation and gene expression data download from Bgee database, and TopAnat analysis: GO-like enrichment of anatomical terms, mapped to genes by expression patterns.

This package provides a collection of tools for doing various analyses of single-cell RNA-seq gene expression data, with a focus on quality control.

Genome level Trellis graph visualizes genomic data conditioned by genomic categories (e.g. chromosomes). For each genomic category, multiple dimensional data which are represented as tracks describe different features from different aspects. This package provides high flexibility to arrange genomic categories and to add self-defined graphics in the plot.

This package provides methods to convert between Python AnnData objects and SingleCellExperiment objects. These are primarily intended for use by downstream Bioconductor packages that wrap Python methods for single-cell data analysis. It also includes functions to read and write H5AD files used for saving AnnData objects to disk.

Explore, diagnose, and compare variant calls using filters. The VariantTools package supports a workflow for loading data, calling single sample variants and tumor-specific somatic mutations or other sample-specific variant types (e.g., RNA editing). Most of the functions operate on alignments (BAM files) or datasets of called variants. The user is expected to have already aligned the reads with a separate tool, e.g., GSNAP via gmapR.

This package provides the output of running various transcript abundance quantifiers on a set of 6 RNA-seq samples from the GEUVADIS project. The quantifiers were Cufflinks, RSEM, kallisto, Salmon and Sailfish. Alevin example output is also included.

This package provides a simple interface to and data from the Human Protein Atlas project.

This package contains the basic methods needed to generate interactive Shiny-based display methods for Bioconductor objects.

This package provides tools to parse Illumina Sequence Analysis Viewer (SAV) files, access data, and generate QC plots.

This package implements clustering of microarray gene expression profiles according to functional annotations. For each term genes are annotated to, splits into two subclasses are computed and a significance of the supporting gene set is determined.

This package provides memory efficient S4 classes for storing sequences "externally" (behind an R external pointer, or on disk).

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.