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gcapc: GC effects aware peak caller

Introduction

ChIP-seq has been widely utilized as the standard technology to detect protein binding regions, where peak calling algorithms were developed particularly to serve the analysis. Existing peak callers lack of power on ranking peaks' significance due to sequencing technology might undergo sequence context biases, e.g. GC bias. gcapc is designed to address this deficiency by modeling GC effects into peak calling.

Installation

gcapc is an R/Bioconductor package, which can be installed with source code documented in GitHub or simply through Bioconductor.

If GitHub source installation is selected, make sure dependency R packages are pre-installed as shown in the DESCRIPTION file. Then, install gcapc with following code.

library(devtools)
install_github("tengmx/gcapc")

Alternatively, installation through Bioconductor is as simple as follows.

source("https://bioconductor.org/biocLite.R")
biocLite("gcapc")

Using gcapc

First, load the package into R.

library(gcapc)

Then, follow the steps introduced in the package vignette to estimate GC-bias or peak calling.

Help

You are very welcome to leave any questions/bug messages at GitHub issues.