GenoGAM

DOI: 10.18129/B9.bioc.GenoGAM    

This package is for version 3.11 of Bioconductor; for the stable, up-to-date release version, see GenoGAM.

A GAM based framework for analysis of ChIP-Seq data

Bioconductor version: 3.11

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>

Installation

To install this package, start R (version "4.0") and enter:

if (!requireNamespace("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")

 

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

Details

biocViews	ChIPSeq, ChipOnChip, DifferentialExpression, DifferentialPeakCalling, Epigenetics, Genetics, ImmunoOncology, Regression, Software, WholeGenome
Version	2.6.0
In Bioconductor since	BioC 3.3 (R-3.3) (4.5 years)
License	GPL-2
Depends	R (>= 3.5), SummarizedExperiment(>= 1.1.19), HDF5Array(>= 1.8.0), rhdf5(>= 2.21.6), S4Vectors(>= 0.23.18), 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
LinkingTo	Rcpp, RcppArmadillo
Suggests	BiocStyle, chipseq(>= 1.21.2), LSD (>= 3.0.0), genefilter(>= 1.54.2), ggplot2 (>= 2.1.0), testthat, knitr, rmarkdown
SystemRequirements
Enhances
URL	https://github.com/gstricker/GenoGAM
BugReports	https://github.com/gstricker/GenoGAM/issues
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report

Package Archives

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

Source Package	GenoGAM_2.6.0.tar.gz
Windows Binary	GenoGAM_2.6.0.zip (32- & 64-bit)
macOS 10.13 (High Sierra)	GenoGAM_2.6.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/GenoGAM
Source Repository (Developer Access)	git clone [email protected]:packages/GenoGAM
Package Short Url	https://bioconductor.org/packages/GenoGAM/
Package Downloads Report	Download Stats