gstricker/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.

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Package details

AuthorGeorg Stricker [aut, cre], Alexander Engelhardt [aut], Julien Gagneur [aut]
Bioconductor views ChIPSeq ChipOnChip DifferentialExpression DifferentialPeakCalling Epigenetics Genetics ImmunoOncology Regression WholeGenome
MaintainerGeorg Stricker <>
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
gstricker/GenoGAM documentation built on July 15, 2019, 7:39 p.m.