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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.
GenoGAM
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This package is for version 3.4 of Bioconductor; for the stable, up-to-date release version, see GenoGAM.
A GAM based framework for analysis of ChIP-Seq data
Bioconductor version: 3.4
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")
| R Script | GenoGAM: Genome-wide generalized additive models | |
| 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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