Bioconductor version: Release (3.11)
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 "4.0") and enter:
if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install("gcapc")
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:
browseVignettes("gcapc")
HTML | R Script | The gcapc user's guide |
Reference Manual | ||
Text | NEWS |
biocViews | BatchEffect, ChIPSeq, PeakDetection, Sequencing, Software |
Version | 1.12.0 |
In Bioconductor since | BioC 3.5 (R-3.4) (3.5 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 |
LinkingTo | |
Suggests | BiocStyle, knitr, rmarkdown, BSgenome.Hsapiens.UCSC.hg19, BSgenome.Mmusculus.UCSC.mm10 |
SystemRequirements | |
Enhances | |
URL | https://github.com/tengmx/gcapc |
Depends On Me | |
Imports Me | |
Suggests Me | |
Links To Me | |
Build Report |
Follow Installation instructions to use this package in your R session.
Source Package | gcapc_1.12.0.tar.gz |
Windows Binary | gcapc_1.12.0.zip |
macOS 10.13 (High Sierra) | gcapc_1.12.0.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/gcapc |
Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/gcapc |
Package Short Url | https://bioconductor.org/packages/gcapc/ |
Package Downloads Report | Download Stats |
Old Source Packages for BioC 3.11 | Source Archive |
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