This package provides visualization tools for flow cytometry data.

This package provides full genome sequences for Danio rerio (Zebrafish) as provided by UCSC (danRer10, Sep. 2014) and stored in Biostrings objects.

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

The ASAFE package contains a collection of functions that can be used to carry out an EM (Expectation–maximization) algorithm to estimate ancestry-specific allele frequencies for a bi-allelic genetic marker, e.g. an SNP (single nucleotide polymorphism) from genotypes and ancestry pairs.

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

This package provides delayed computation of a matrix of scaled and centered values. The result is equivalent to using the scale function but avoids explicit realization of a dense matrix during block processing. This permits greater efficiency in common operations, most notably matrix multiplication.

This package implements widgets to provide user interfaces.

The sparse nature of single cell epigenomics data can be overruled using probabilistic modelling methods such as Latent Dirichlet Allocation (LDA). This package allows the probabilistic modelling of cis-regulatory topics (cisTopics) from single cell epigenomics data, and includes functionalities to identify cell states based on the contribution of cisTopics and explore the nature and regulatory proteins driving them.

This package implements `import()` and `export()` standard generics for importing and exporting biological data formats. `import()` supports whole-file as well as chunk-wise iterative import. The `import()` interface optionally provides a standard mechanism for 'lazy' access via `filter()` (on row or element-like components of the file resource), `select()` (on column-like components of the file resource) and `collect()`. The `import()` interface optionally provides transparent access to remote (e.g. via https) as well as local access. Developers can register a file extension, e.g., `.loom` for dispatch from character-based URIs to specific `import()` / `export()` methods based on classes representing file types, e.g., `LoomFile()`.

This is a package to support identification of markers of rare cell types by looking at genes whose expression is confined in small regions of the expression space.

This package provides tools to produce a graphical display, as a heat map, of measures of pairwise linkage disequilibria between SNPs. Users may optionally include the physical locations or genetic map distances of each SNP on the plot.

This package provides a dplyr-like interface for interacting with the common Bioconductor classes Ranges and GenomicRanges. By providing a grammatical and consistent way of manipulating these classes their accessibility for new Bioconductor users is hopefully increased.

This package provides a subset of BAM files untreated1.bam (single-end reads) and untreated3.bam (paired-end reads) from "Pasilla" experiment (Pasilla knock-down by Brooks et al., Genome Research 2011). See the vignette in the pasilla data package for how BAM files untreated1.bam and untreated3.bam were obtained from the RNA-Seq read sequence data that is provided by NCBI Gene Expression Omnibus under accession numbers GSM461176 to GSM461181. It also contains the DNA sequence for fly chromosome 4 to which the reads can be mapped.

MethylKit is an R package for DNA methylation analysis and annotation from high-throughput bisulfite sequencing. The package is designed to deal with sequencing data from Reduced representation bisulfite sequencing (RRBS) and its variants, but also target-capture methods and whole genome bisulfite sequencing. It also has functions to analyze base-pair resolution 5hmC data from experimental protocols such as oxBS-Seq and TAB-Seq.

This package contains the Mus.musculus object to access data from several related annotation packages.

This package provides a method for finding an enrichment of cancer simple somatic mutations (SNVs and Indels) in functional elements across the human genome. ActiveDriverWGS detects coding and noncoding driver elements using whole genome sequencing data.

This package provides a database of SIFT predictions for Homo sapiens dbSNP build 132.

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 provides a data-driven test for the assumptions of quantile normalization using raw data such as objects that inherit eSets (e.g. ExpressionSet, MethylSet). Group level information about each sample (such as Tumor / Normal status) must also be provided because the test assesses if there are global differences in the distributions between the user-defined groups.

biomaRt provides an interface to a growing collection of databases implementing the http://www.biomart.org. The package enables retrieval of large amounts of data in a uniform way without the need to know the underlying database schemas or write complex SQL queries. Examples of BioMart databases are Ensembl, COSMIC, Uniprot, HGNC, Gramene, Wormbase and dbSNP mapped to Ensembl. These major databases give biomaRt users direct access to a diverse set of data and enable a wide range of powerful online queries from gene annotation to database mining.

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 gene-level read counts from RNA-Seq for gallein-treated and control zebrafish.

Many methods allow us to extract biological activities from omics data using information from prior knowledge resources, reducing the dimensionality for increased statistical power and better interpretability. decoupleR is a Bioconductor package containing different statistical methods to extract these signatures within a unified framework. decoupleR allows the user to flexibly test any method with any resource. It incorporates methods that take into account the sign and weight of network interactions. decoupleR can be used with any omic, as long as its features can be linked to a biological process based on prior knowledge. For example, in transcriptomics gene sets regulated by a transcription factor, or in phospho-proteomics phosphosites that are targeted by a kinase.

The package ABarray is designed to work with Applied Biosystems whole genome microarray platform, as well as any other platform whose data can be transformed into expression data matrix. Functions include data preprocessing, filtering, control probe analysis, statistical analysis in one single function. A graphical user interface (GUI) is also provided. The raw data, processed data, graphics output and statistical results are organized into folders according to the analysis settings used.