This package provides plotting functions, frameshift detection and parsing of genetic sequencing data from ribosome profiling experiments.

This package provides a package containing an environment representing the HG_U95Av2.CDF file.

This package provides tools to identify cell populations in Flow Cytometry data using non-parametric clustering and segmented-regression-based change point detection.

This package provides a pipeline for analysing Capture Hi-C data.

This package defines coerce methods for microarray data objects.

This package provides utilities for Receiver Operating Characteristic (ROC) curves, with a focus on micro arrays.

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 Affymetrix Human Genome U95 Set annotation data (hgu95av2) assembled using data from public data repositories.

This package provides an integrated web interface for doing microarray analysis using several of the Bioconductor packages. It is intended to be deployed as a centralized bioinformatics resource for use by many users. Currently only Affymetrix oligonucleotide analysis is supported.

This package provides a framework for processing and visualization of chromatographically separated and single-spectra mass spectral data. It imports from AIA/ANDI NetCDF, mzXML, mzData and mzML files. It preprocesses data for high-throughput, untargeted analyte profiling.

The semantic comparisons of Gene Ontology (GO) annotations provide quantitative ways to compute similarities between genes and gene groups, and have became important basis for many bioinformatics analysis approaches. GOSemSim is an R package for semantic similarity computation among GO terms, sets of GO terms, gene products and gene clusters.

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 an annotation database of Homo sapiens genome data. It is derived from the UCSC hg19 genome and based on the "knownGene" track. The database is exposed as a TxDb object.

This package is a collection of Strand-seq data. The main purpose is to demonstrate functionalities of the breakpointR package.

This package provides full masked genome sequences for Drosophila melanogaster (Fly) as provided by UCSC (dm3, April 2006) and stored in Biostrings objects. The sequences are the same as in BSgenome.Dmelanogaster.UCSC.dm3, 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 provides functions for visualizing hypergraphs.

This R package provides tools for handling genomic interaction data, such as ChIA-PET/Hi-C, annotating genomic features with interaction information and producing various plots and statistics.

The purpose of this GO.db annotation package is to provide detailed information about the latest version of the Gene Ontologies.

This package provides code for generating Annotation packages and their databases. Packages produced are intended to be used with AnnotationDbi.

This library contains functions that calculate various statistics of differential expression for microarray data, including t statistics, fold change, F statistics, SAM, moderated t and F statistics and B statistics. It also implements a new methodology called DEDS (Differential Expression via Distance Summary), which selects differentially expressed genes by integrating and summarizing a set of statistics using a weighted distance approach.

The package ABAEnrichment is designed to test for enrichment of user defined candidate genes in the set of expressed genes in different human brain regions. The core function aba_enrich integrates the expression of the candidate gene set (averaged across donors) and the structural information of the brain using an ontology, both provided by the Allen Brain Atlas project.

InferCNV is used to explore tumor single cell RNA-Seq data to identify evidence for somatic large-scale chromosomal copy number alterations, such as gains or deletions of entire chromosomes or large segments of chromosomes. This is done by exploring expression intensity of genes across positions of a tumor genome in comparison to a set of reference "normal" cells. A heatmap is generated illustrating the relative expression intensities across each chromosome, and it often becomes readily apparent as to which regions of the tumor genome are over-abundant or less-abundant as compared to that of normal cells.

This package provides tools to visualize oligonucleotide patterns and sequence motif occurrences across a large set of sequences centred at a common reference point and sorted by a user defined feature.

M3C is a consensus clustering algorithm that uses a Monte Carlo simulation to eliminate overestimation of K and can reject the null hypothesis K=1.