GenoGAM

This package is for version 3.9 of Bioconductor. This package has been removed from Bioconductor. For the last stable, up-to-date release version, see GenoGAM.

A GAM based framework for analysis of ChIP-Seq data


Bioconductor version: 3.9

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 protonmail.com>

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

Installation

To install this package, start R (version "3.6") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("GenoGAM")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

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

browseVignettes("GenoGAM")
Modeling ChIP-Seq data with GenoGAM 2.0: A Genome-wide generalized additive model HTML R Script
Reference Manual PDF
NEWS Text

Details

biocViews ChIPSeq, ChipOnChip, DifferentialExpression, DifferentialPeakCalling, Epigenetics, Genetics, ImmunoOncology, Regression, Software, WholeGenome
Version 2.2.0
In Bioconductor since BioC 3.3 (R-3.3) (8 years)
License GPL-2
Depends R (>= 3.5), SummarizedExperiment(>= 1.1.19), HDF5Array(>= 1.8.0), rhdf5(>= 2.21.6), S4Vectors(>= 0.9.34), Matrix (>= 1.2-8), data.table (>= 1.9.4)
Imports Rcpp (>= 0.12.14), sparseinv (>= 0.1.1), Rsamtools(>= 1.18.2), GenomicRanges(>= 1.23.16), BiocParallel(>= 1.5.17), DESeq2(>= 1.11.23), futile.logger (>= 1.4.1), GenomeInfoDb(>= 1.7.6), GenomicAlignments(>= 1.7.17), IRanges(>= 2.5.30), Biostrings(>= 2.39.14), DelayedArray(>= 0.3.19), methods, stats
System Requirements
URL https://github.com/gstricker/GenoGAM
Bug Reports https://github.com/gstricker/GenoGAM/issues
See More
Suggests BiocStyle, chipseq(>= 1.21.2), LSD (>= 3.0.0), genefilter(>= 1.54.2), ggplot2 (>= 2.1.0), testthat, knitr, rmarkdown
Linking To Rcpp, RcppArmadillo
Enhances
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report Build Report

Package Archives

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

Source Package GenoGAM_2.2.0.tar.gz
Windows Binary GenoGAM_2.2.0.zip (32- & 64-bit)
Mac OS X 10.11 (El Capitan) GenoGAM_2.2.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/GenoGAM
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/GenoGAM
Bioc Package Browser https://code.bioconductor.org/browse/GenoGAM/
Package Short Url https://bioconductor.org/packages/GenoGAM/
Package Downloads Report Download Stats
Old Source Packages for BioC 3.9 Source Archive