RockefellerUniversity/profileplyr: Visualization and annotation of read signal over genomic ranges with profileplyr

Quick and straightforward visualization of read signal over genomic intervals is key for generating hypotheses from sequencing data sets (e.g. ChIP-seq, ATAC-seq, bisulfite/methyl-seq). Many tools both inside and outside of R and Bioconductor are available to explore these types of data, and they typically start with a bigWig or BAM file and end with some representation of the signal (e.g. heatmap). profileplyr leverages many Bioconductor tools to allow for both flexibility and additional functionality in workflows that end with visualization of the read signal.

Getting started

Package details

AuthorTom Carroll and Doug Barrows
Bioconductor views ChIPSeq ChipOnChip Coverage DataImport Sequencing
MaintainerTom Carroll <tc.infomatics@gmail.com>, Doug Barrows <doug.barrows@gmail.com>
LicenseGPL (>= 3)
Version1.7.2
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("RockefellerUniversity/profileplyr")
RockefellerUniversity/profileplyr documentation built on Nov. 11, 2020, 8:28 p.m.