gstricker/fastGenoGAM: 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
Browse package contents
Package details |
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| Author | Georg Stricker [aut, cre], Alexander Engelhardt [aut], Julien Gagneur [aut] |
| Bioconductor views | ChIPSeq ChipOnChip DifferentialExpression DifferentialPeakCalling Epigenetics Genetics Regression WholeGenome |
| Maintainer | Georg Stricker <georg.stricker@in.tum.de> |
| License | GPL-2 |
| Version | 1.99.0 |
| URL | https://github.com/gstricker/GenoGAM |
| Package repository | View on GitHub |
| Installation |
Install the latest version of this package by entering the following in R:
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