GenoGAM: A GAM based framework for analysis of ChIP-Seq data
Version 1.4.0

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.

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
Version1.4.0
URL https://github.com/gstricker/GenoGAM
Package repositoryView on Bioconductor
Installation Install the latest version of this package by entering the following in R:
source("https://bioconductor.org/biocLite.R")
biocLite("GenoGAM")

Try the GenoGAM package in your browser

Any scripts or data that you put into this service are public.

GenoGAM documentation built on May 31, 2017, 2:27 p.m.