To install this package, start R and enter:
## try http:// if https:// URLs are not supported source("https://bioconductor.org/biocLite.R") biocLite("GenoGAM")
In most cases, you don't need to download the package archive at all.
Bioconductor version: Release (3.5)
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")
):
To install this package, start R and enter:
## try http:// if https:// URLs are not supported source("https://bioconductor.org/biocLite.R") biocLite("GenoGAM")
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("GenoGAM")
R Script | GenoGAM: Genome-wide generalized additive models | |
Reference Manual | ||
Text | NEWS |
biocViews | ChIPSeq, DifferentialExpression, DifferentialPeakCalling, Epigenetics, Genetics, Regression, Software |
Version | 1.4.0 |
In Bioconductor since | BioC 3.3 (R-3.3) (1.5 years) |
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 |
Follow Installation instructions to use this package in your R session.
Source Package | GenoGAM_1.4.0.tar.gz |
Windows Binary | GenoGAM_1.4.0.zip |
Mac OS X 10.11 (El Capitan) | GenoGAM_1.4.0.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/GenoGAM |
Package Short Url | http://bioconductor.org/packages/GenoGAM/ |
Package Downloads Report | Download Stats |
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