GenoGAM
This package is for version 3.13 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: 3.13
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("GenoGAM")):
Installation
To install this package, start R (version "4.1") 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 | ||
| NEWS | Text |
Details
| biocViews | ChIPSeq, ChipOnChip, DifferentialExpression, DifferentialPeakCalling, Epigenetics, Genetics, ImmunoOncology, Regression, Software, WholeGenome |
| Version | 2.10.0 |
| 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(>= 0.23.18), 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 |
| 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_2.10.0.tar.gz |
| Windows Binary | GenoGAM_2.10.0.zip |
| macOS 10.13 (High Sierra) | GenoGAM_2.10.0.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 3.13 | Source Archive |