The STRINGdb package provides an R interface to the STRING protein-protein interactions database. STRING is a database of known and predicted protein-protein interactions. The interactions include direct (physical) and indirect (functional) associations. Each interaction is associated with a combined confidence score that integrates the various evidences.

This package provides genome wide annotation for Yeast, primarily based on mapping using ORF identifiers from SGD.

This package efficiently obtains count vectors from indexed bam files. It counts the number of nucleotide sequence reads in given genomic ranges and it computes reads profiles and coverage profiles. It also handles paired-end data.

The data consist of microarrays from 128 different individuals with acute lymphoblastic leukemia (ALL). A number of additional covariates are available. The data have been normalized (using rma) and it is the jointly normalized data that are available here. The data are presented in the form of an exprSet object.

This package is a 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.

This package models a RESTful service as if it were a nested R list.

This package provides an interface to simulate metabolic reconstruction from the BiGG database and other metabolic reconstruction databases. The package facilitates flux balance analysis (FBA) and the sampling of feasible flux distributions. Metabolic networks and estimated fluxes can be visualized with hypergraphs.

This package provides tools to analyze and visualize Illumina Infinium methylation arrays.

This package contains a SummarizedExperiment from the Yu et al. (2013) paper that performed the rat BodyMap across 11 organs and 4 developmental stages. Raw FASTQ files were downloaded and mapped using STAR. Data is available on ExperimentHub as a data package.

Starting with a BAM file, this package provides the necessary functions for quality assessment, read start position recalibration, the counting of genomic sequence reads on CDS, 3'UTR, and 5'UTR, and plotting of count data: pairs, log fold-change, codon frequency and coverage assessment, principal component analysis on codon coverage.

This package contains functions and classes that are needed by arrayCGH packages.

This package provides a fairly extensive and comprehensive interface to the graph algorithms contained in the Boost library.

This package provides tools for calculating the Reproducibility-Optimized Test Statistic (ROTS) for differential testing in omics data.

This package provides 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. https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE110554.

This package provides tools to support the analysis of RNA-seq expression data or other similar kind of data. It provides exploratory plots to evaluate saturation, count distribution, expression per chromosome, type of detected features, features length, etc. It also supports the analysis of differential expression between two experimental conditions with no parametric assumptions.

This package defines data structures for linkage disequilibrium (LD) measures in populations. Its purpose is to simplify handling of existing population-level data for the purpose of flexibly defining LD blocks.

This package is an R package that offers models and tools for subject level analysis of X chromosome inactivation (XCI) and XCI-escape inference.

This package provides tools for discriminative motif discovery in high throughput genetic sequencing data sets using regression methods.

ChIPComp implements a statistical method for quantitative comparison of multiple ChIP-seq datasets. It detects differentially bound sharp binding sites across multiple conditions considering matching control in ChIP-seq datasets.

This package contains whole-genome single cell sequencing data for demonstration purposes in the AneuFinder package.

This package provides S4 data structures and basic functions to deal with flow cytometry data.

The QFeatures infrastructure enables the management and processing of quantitative features for high-throughput mass spectrometry assays. It provides a familiar Bioconductor user experience to manages quantitative data across different assay levels (such as peptide spectrum matches, peptides and proteins) in a coherent and tractable format.

This package expands the usethis package with the goal of helping automate the process of creating R packages for Bioconductor or making them Bioconductor-friendly.

This package contains the functions to find the gene expression modules that represent the drivers of Kauffman's attractor landscape. The modules are the core attractor pathways that discriminate between different cell types of groups of interest. Each pathway has a set of synexpression groups, which show transcriptionally-coordinated changes in gene expression.