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

This package provides tools for estimating variance-mean dependence in count data from high-throughput genetic sequencing assays and for testing for differential expression based on a model using the negative binomial distribution.

This package provides more than 2000 annotated position frequency matrices from nine public sources, for multiple organisms.

This package provides functions for plotting genomic data.

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 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 examples and code that make use of the different graph related packages produced by Bioconductor.

This package provides tools for statistical analysis of assembled transcriptomes, including flexible differential expression analysis, visualization of transcript structures, and matching of assembled transcripts to annotation.

The Structstrings package implements the widely used dot bracket annotation for storing base pairing information in structured RNA. Structstrings uses the infrastructure provided by the Biostrings package and derives the DotBracketString and related classes from the BString class. From these, base pair tables can be produced for in depth analysis. In addition, the loop indices of the base pairs can be retrieved as well. For better efficiency, information conversion is implemented in C, inspired to a large extend by the ViennaRNA package.

This is a package for segmentation of allele-specific DNA copy number data and detection of regions with abnormal copy number within each parental chromosome. Both tumor-normal paired and tumor-only analyses are supported.

This package provides a manifest for Illumina's 450k array data.

This package provides functions for pathway analysis based on the REACTOME pathway database. It implements enrichment analysis, gene set enrichment analysis and several functions for visualization.

Store minor allele frequency data from the Phase 1 of the 1000 Genomes Project for the human genome version hs37d5.

This is a tool for human B-cell context-specific transcriptional regulatory network. In addition, this package provides a human normal B-cells dataset for the examples in package viper.

The AnVIL is a cloud computing resource developed in part by the National Human Genome Research Institute. The AnVIL package provides end-user and developer functionality. AnVIL provides fast binary package installation, utilities for working with Terra/AnVIL table and data resources, and convenient functions for file movement to and from Google cloud storage. For developers, AnVIL provides programmatic access to the Terra, Leonardo, Rawls, Dockstore, and Gen3 RESTful programming interface, including helper functions to transform JSON responses to formats more amenable to manipulation in R.

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 contains class definitions for two-color spotted microarray data. It also includes functions for data input, diagnostic plots, normalization and quality checking.

This package provides a client for the Bioconductor ExperimentHub web resource. ExperimentHub provides a central location where curated data from experiments, publications or training courses can be accessed. Each resource has associated metadata, tags and date of modification. The client creates and manages a local cache of files retrieved enabling quick and reproducible access.

This package provides classes for holding and manipulating Illumina methylation data. Based on eSet, it can contain MIAME information, sample information, feature information, and multiple matrices of data. An "intelligent" import function, methylumiR can read the Illumina text files and create a MethyLumiSet. methylumIDAT can directly read raw IDAT files from HumanMethylation27 and HumanMethylation450 microarrays. Normalization, background correction, and quality control features for GoldenGate, Infinium, and Infinium HD arrays are also included.

This R package is for multi-sample transcript discovery and quantification using long read RNA-Seq data. You can use bambu after read alignment to obtain expression estimates for known and novel transcripts and genes. The output from bambu can directly be used for visualisation and downstream analysis, such as differential gene expression or transcript usage.

Perform large scale genomic data retrieval and functional annotation retrieval. This package aims to provide users with a standardized way to automate genome, proteome, RNA, coding sequence (CDS), GFF, and metagenome retrieval from NCBI RefSeq, NCBI Genbank, ENSEMBL, and UniProt databases. Furthermore, an interface to the BioMart database allows users to retrieve functional annotation for genomic loci. In addition, users can download entire databases such as NCBI RefSeq, NCBI nr, NCBI nt, NCBI Genbank, etc with only one command.

This package aims to make NMR spectroscopy data analysis as easy as possible. It only requires a small set of functions to perform an entire analysis. Speaq offers the possibility of raw spectra alignment and quantitation but also an analysis based on features whereby the spectra are converted to peaks which are then grouped and turned into features. These features can be processed with any number of statistical tools either included in speaq or available elsewhere on CRAN.

This package implements some simple graph handling capabilities for R.

This package provides a database of PolyPhen predictions for Homo sapiens dbSNP build 131.