Analyze and visualize Mutation Annotation Format (MAF) files from large scale sequencing studies. This package provides various functions to perform most commonly used analyses in cancer genomics and to create feature rich customizable visualzations with minimal effort.

This package provides a collection of tools for performing category analysis.

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

This package is designed to store minor allele frequency data. It retrieves this data from the Genome Aggregation Database (gnomAD version 3.1.2) for the human genome version GRCh38.

This package implements the gene expression anti-profiles method. Anti-profiles are a new approach for developing cancer genomic signatures that specifically take advantage of gene expression heterogeneity. They explicitly model increased gene expression variability in cancer to define robust and reproducible gene expression signatures capable of accurately distinguishing tumor samples from healthy controls.

This package exposes a C elegans annotation database generated from UCSC by exposing these as TxDb objects.

This package provides a collection of tools for cancer genomic data clustering analyses, including those for single cell RNA-seq. Cell clustering and feature gene selection analysis employ Bayesian (and maximum likelihood) non-negative matrix factorization (NMF) algorithm. Input data set consists of RNA count matrix, gene, and cell bar code annotations. Analysis outputs are factor matrices for multiple ranks and marginal likelihood values for each rank. The package includes utilities for downstream analyses, including meta-gene identification, visualization, and construction of rank-based trees for clusters.

This package provides a function to infer pathway activity from gene expression. It contains the linear model inferred in the publication "Perturbation-response genes reveal signaling footprints in cancer gene expression".

This package provides supporting data for the TCGAbiolinksGUI package.

This is a package for significance analysis of Microarrays for differential expression analysis, RNAseq data and related problems.

This package provides lower-level functionality to interface with Google Cloud Platform tools. gcloud and gsutil are both supported. The functionality provided centers around utilities for the AnVIL platform.

This is a package for biclustering analysis and exploration of results.

This package provides functions to estimate variance-mean dependence in count data from high-throughput nucleotide sequencing assays and test for differential expression based on a model using the negative binomial distribution.

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

This package provides Bayesian PCA, Probabilistic PCA, Nipals PCA, Inverse Non-Linear PCA and the conventional SVD PCA. A cluster based method for missing value estimation is included for comparison. BPCA, PPCA and NipalsPCA may be used to perform PCA on incomplete data as well as for accurate missing value estimation. A set of methods for printing and plotting the results is also provided. All PCA methods make use of the same data structure (pcaRes) to provide a common interface to the PCA results.

The package implements an algorithm for fast gene set enrichment analysis. Using the fast algorithm makes more permutations and gets more fine grained p-values, which allows using accurate standard approaches to multiple hypothesis correction.

This package provides a manifest package for Illumina's EPIC v2.0 methylation arrays. The version 2 covers more than 935K CpG sites in the human genome hg38. It is an update of the original EPIC v1.0 array (i.e., the 850K methylation array).

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.

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.

The msa package provides a unified R/Bioconductor interface to the multiple sequence alignment algorithms ClustalW, ClustalOmega, and Muscle. All three algorithms are integrated in the package, therefore, they do not depend on any external software tools and are available for all major platforms. The multiple sequence alignment algorithms are complemented by a function for pretty-printing multiple sequence alignments using the LaTeX package TeXshade.

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

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 tools for Bayesian integrated analysis of Affymetrix GeneChips.

This package creates karyotype plots of arbitrary genomes and offers a complete set of functions to plot arbitrary data on them. It mimics many R base graphics functions coupling them with a coordinate change function automatically mapping the chromosome and data coordinates into the plot coordinates.