-
recipe
bioconductor-genogam¶ 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.
- Homepage
https://bioconductor.org/packages/3.9/bioc/html/GenoGAM.html
- License
GPL-2
- Recipe
- Links
biotools: genogam, doi: 10.1093/bioinformatics/btx150
-
package
bioconductor-genogam¶ 
- Versions
2.2.0-1, 2.0.2-0, 1.8.0-0, 1.6.0-0
- Depends
bioconductor-biocparallel >=1.18.0,<1.19.0
bioconductor-biostrings >=2.52.0,<2.53.0
bioconductor-delayedarray >=0.10.0,<0.11.0
bioconductor-deseq2 >=1.24.0,<1.25.0
bioconductor-genomeinfodb >=1.20.0,<1.21.0
bioconductor-genomicalignments >=1.20.0,<1.21.0
bioconductor-genomicranges >=1.36.0,<1.37.0
bioconductor-hdf5array >=1.12.0,<1.13.0
bioconductor-iranges >=2.18.0,<2.19.0
bioconductor-rhdf5 >=2.28.0,<2.29.0
bioconductor-rsamtools >=2.0.0,<2.1.0
bioconductor-s4vectors >=0.22.0,<0.23.0
bioconductor-summarizedexperiment >=1.14.0,<1.15.0
libgcc-ng >=7.3.0
libstdcxx-ng >=7.3.0
r-base >=3.6,<3.7.0a0
r-data.table >=1.9.4
r-futile.logger >=1.4.1
r-matrix >=1.2-8
r-rcpp >=0.12.14
r-sparseinv >=0.1.1
- Required By
Installation
With an activated Bioconda channel (see 2. Set up channels), install with:
conda install bioconductor-genogam
and update with:
conda update bioconductor-genogam
or use the docker container:
docker pull quay.io/biocontainers/bioconductor-genogam:<tag>
(see bioconductor-genogam/tags for valid values for
<tag>)
Link to this page¶
Render an 
badge with the following MarkDown:
[](http://bioconda.github.io/recipes/bioconductor-genogam/README.html)