BRGenomics: Tools for the Efficient Analysis of High-Resolution Genomics Data

This package provides useful and efficient utilites for the analysis of high-resolution genomic data using standard Bioconductor methods and classes. BRGenomics is feature-rich and simplifies a number of post-alignment processing steps and data handling. Emphasis is on efficient analysis of multiple datasets, with support for normalization and blacklisting. Included are functions for: spike-in normalizing data; generating basepair-resolution readcounts and coverage data (e.g. for heatmaps); importing and processing bam files (e.g. for conversion to bigWig files); generating metaplots/metaprofiles (bootstrapped mean profiles) with confidence intervals; conveniently calling DESeq2 without using sample-blind estimates of genewise dispersion; among other features.

Package details

AuthorMike DeBerardine [aut, cre]
Bioconductor views ATACSeq ChIPSeq Coverage DataImport GeneExpression GeneRegulation Normalization RNASeq Sequencing Software Transcription
MaintainerMike DeBerardine <mike.deberardine@gmail.com>
LicenseArtistic-2.0
Version1.2.0
URL https://mdeber.github.io
Package repositoryView on Bioconductor
Installation Install the latest version of this package by entering the following in R:
if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("BRGenomics")

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BRGenomics documentation built on Nov. 8, 2020, 8:03 p.m.