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profileplyr

Visualization and annotation of read signal over genomic ranges with profileplyr


Bioconductor version: Release (3.18)

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.

Author: Tom Carroll and Doug Barrows

Maintainer: Tom Carroll <tc.infomatics at gmail.com>, Doug Barrows <doug.barrows at gmail.com>

Citation (from within R, enter citation("profileplyr")):

Installation

To install this package, start R (version "4.3") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("profileplyr")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("profileplyr")
Visualization and annotation of read signal over genomic ranges with profileplyr HTML R Script
Reference Manual PDF
NEWS Text

Details

biocViews ChIPSeq, ChipOnChip, Coverage, DataImport, Sequencing, Software
Version 1.18.0
In Bioconductor since BioC 3.9 (R-3.6) (5 years)
License GPL (>= 3)
Depends R (>= 3.6), BiocGenerics, SummarizedExperiment
Imports GenomicRanges, stats, soGGi, methods, utils, S4Vectors, R.utils, dplyr, magrittr, tidyr, IRanges, rjson, ChIPseeker, GenomicFeatures, TxDb.Hsapiens.UCSC.hg19.knownGene, TxDb.Hsapiens.UCSC.hg38.knownGene, TxDb.Mmusculus.UCSC.mm10.knownGene, TxDb.Mmusculus.UCSC.mm9.knownGene, org.Hs.eg.db, org.Mm.eg.db, rGREAT, pheatmap, ggplot2, EnrichedHeatmap, ComplexHeatmap, grid, circlize, BiocParallel, rtracklayer, GenomeInfoDb, grDevices, rlang, tiff, Rsamtools
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Suggests BiocStyle, testthat, knitr, rmarkdown, png, Cairo
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Package Archives

Follow Installation instructions to use this package in your R session.

Source Package profileplyr_1.18.0.tar.gz
Windows Binary profileplyr_1.18.0.zip
macOS Binary (x86_64) profileplyr_1.18.0.tgz
macOS Binary (arm64) profileplyr_1.18.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/profileplyr
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/profileplyr
Bioc Package Browser https://code.bioconductor.org/browse/profileplyr/
Package Short Url https://bioconductor.org/packages/profileplyr/
Package Downloads Report Download Stats