Bioconductor-mirror/GenoGAM: A GAM based framework for analysis of ChIP-Seq data

This package allows statistical analysis of genome-wide data with smooth functions using generalized additive models based on the implementation from the R-package 'mgcv'. It provides methods for the statistical analysis of ChIP-Seq data including inference of protein occupancy, and pointwise and region-wise differential analysis. Estimation of dispersion and smoothing parameters is performed by cross-validation. Scaling of generalized additive model fitting to whole chromosomes is achieved by parallelization over overlapping genomic intervals.

Getting started

Package details

AuthorGeorg Stricker [aut, cre], Alexander Engelhardt [aut], Julien Gagneur [aut]
Bioconductor views ChIPSeq DifferentialExpression DifferentialPeakCalling Epigenetics Genetics Regression
MaintainerGeorg Stricker <[email protected]>
LicenseGPL-2
Version1.5.4
URL https://github.com/gstricker/GenoGAM
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("devtools")
library(devtools)
install_github("Bioconductor-mirror/GenoGAM")
Bioconductor-mirror/GenoGAM documentation built on Aug. 17, 2017, 3:44 p.m.