recipe bioconductor-dmrseq

Detection and inference of differentially methylated regions from Whole Genome Bisulfite Sequencing

Homepage:

https://bioconductor.org/packages/3.18/bioc/html/dmrseq.html

License:

MIT + file LICENSE

Recipe:

/bioconductor-dmrseq/meta.yaml

This package implements an approach for scanning the genome to detect and perform accurate inference on differentially methylated regions from Whole Genome Bisulfite Sequencing data. The method is based on comparing detected regions to a pooled null distribution, that can be implemented even when as few as two samples per population are available. Region-level statistics are obtained by fitting a generalized least squares (GLS) regression model with a nested autoregressive correlated error structure for the effect of interest on transformed methylation proportions.

package bioconductor-dmrseq

versions:

1.22.0-0,  1.20.0-0,  1.18.0-0,  1.14.0-0,  1.12.0-0,  1.10.0-1,  1.10.0-0,  1.8.0-0,  1.6.0-0, 

1.22.0-0,  1.20.0-0,  1.18.0-0,  1.14.0-0,  1.12.0-0,  1.10.0-1,  1.10.0-0,  1.8.0-0,  1.6.0-0,  1.4.9-0,  1.2.1-0

depends bioconductor-annotationhub:

>=3.10.0,<3.11.0

depends bioconductor-annotatr:

>=1.28.0,<1.29.0

depends bioconductor-biocparallel:

>=1.36.0,<1.37.0

depends bioconductor-bsseq:

>=1.38.0,<1.39.0

depends bioconductor-bumphunter:

>=1.44.0,<1.45.0

depends bioconductor-delayedmatrixstats:

>=1.24.0,<1.25.0

depends bioconductor-genomeinfodb:

>=1.38.0,<1.39.0

depends bioconductor-genomicranges:

>=1.54.0,<1.55.0

depends bioconductor-iranges:

>=2.36.0,<2.37.0

depends bioconductor-rtracklayer:

>=1.62.0,<1.63.0

depends bioconductor-s4vectors:

>=0.40.0,<0.41.0

depends r-base:

>=4.3,<4.4.0a0

depends r-ggplot2:

depends r-locfit:

depends r-matrixstats:

depends r-nlme:

depends r-outliers:

depends r-rcolorbrewer:

requirements:

Installation

You need a conda-compatible package manager (currently either micromamba, mamba, or conda) and the Bioconda channel already activated (see set-up-channels).

While any of above package managers is fine, it is currently recommended to use either micromamba or mamba (see here for installation instructions). We will show all commands using mamba below, but the arguments are the same for the two others.

Given that you already have a conda environment in which you want to have this package, install with:

   mamba install bioconductor-dmrseq

and update with::

   mamba update bioconductor-dmrseq

To create a new environment, run:

mamba create --name myenvname bioconductor-dmrseq

with myenvname being a reasonable name for the environment (see e.g. the mamba docs for details and further options).

Alternatively, use the docker container:

   docker pull quay.io/biocontainers/bioconductor-dmrseq:<tag>

(see `bioconductor-dmrseq/tags`_ for valid values for ``<tag>``)

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