To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("GenoGAM")

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GenoGAM

 

   

A GAM based framework for analysis of ChIP-Seq data

Bioconductor version: Release (3.4)

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.

Author: Georg Stricker [aut, cre], Alexander Engelhardt [aut], Julien Gagneur [aut]

Maintainer: Georg Stricker <georg.stricker at in.tum.de>

Citation (from within R, enter citation("GenoGAM")):

Installation

To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("GenoGAM")

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("GenoGAM")

 

PDF R Script GenoGAM: Genome-wide generalized additive models
PDF   Reference Manual
Text   NEWS

Details

biocViews ChIPSeq, DifferentialExpression, DifferentialPeakCalling, Epigenetics, Genetics, Regression, Software
Version 1.2.1
In Bioconductor since BioC 3.3 (R-3.3) (1 year)
License GPL-2
Depends R (>= 3.3), Rsamtools(>= 1.18.2), SummarizedExperiment(>= 1.1.19), GenomicRanges(>= 1.23.16), methods
Imports BiocParallel(>= 1.5.17), data.table (>= 1.9.4), DESeq2(>= 1.11.23), futile.logger (>= 1.4.1), GenomeInfoDb(>= 1.7.6), GenomicAlignments(>= 1.7.17), IRanges(>= 2.5.30), mgcv (>= 1.8), reshape2 (>= 1.4.1), S4Vectors(>= 0.9.34), Biostrings(>= 2.39.14)
LinkingTo
Suggests BiocStyle, chipseq(>= 1.21.2), LSD (>= 3.0.0), genefilter(>= 1.54.2), ggplot2 (>= 2.1.0), testthat, knitr
SystemRequirements
Enhances
URL https://github.com/gstricker/GenoGAM
BugReports https://github.com/gstricker/GenoGAM/issues
Depends On Me
Imports Me
Suggests Me
Build Report  

Package Archives

Follow Installation instructions to use this package in your R session.

Package Source GenoGAM_1.2.1.tar.gz
Windows Binary GenoGAM_1.2.1.zip
Mac OS X 10.9 (Mavericks) GenoGAM_1.2.1.tgz
Subversion source (username/password: readonly)
Git source https://github.com/Bioconductor-mirror/GenoGAM/tree/release-3.4
Package Short Url http://bioconductor.org/packages/GenoGAM/
Package Downloads Report Download Stats

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