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GC Aware Peak Caller

Bioconductor version: Release (3.18)

Peak calling for ChIP-seq data with consideration of potential GC bias in sequencing reads. GC bias is first estimated with generalized linear mixture models using effective GC strategy, then applied into peak significance estimation.

Author: Mingxiang Teng and Rafael A. Irizarry

Maintainer: Mingxiang Teng <tengmx at gmail.com>

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


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

if (!require("BiocManager", quietly = TRUE))


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


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

The gcapc user's guide HTML R Script
Reference Manual PDF


biocViews BatchEffect, ChIPSeq, PeakDetection, Sequencing, Software
Version 1.26.0
In Bioconductor since BioC 3.5 (R-3.4) (7 years)
License GPL-3
Depends R (>= 3.4)
Imports BiocGenerics, GenomeInfoDb, S4Vectors, IRanges, Biostrings, BSgenome, GenomicRanges, Rsamtools, GenomicAlignments, matrixStats, MASS, splines, grDevices, graphics, stats, methods
System Requirements
URL https://github.com/tengmx/gcapc
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Suggests BiocStyle, knitr, rmarkdown, BSgenome.Hsapiens.UCSC.hg19, BSgenome.Mmusculus.UCSC.mm10
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Package Archives

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

Source Package gcapc_1.26.0.tar.gz
Windows Binary gcapc_1.26.0.zip
macOS Binary (x86_64) gcapc_1.26.0.tgz
macOS Binary (arm64) gcapc_1.26.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/gcapc
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/gcapc
Bioc Package Browser https://code.bioconductor.org/browse/gcapc/
Package Short Url https://bioconductor.org/packages/gcapc/
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