Package Recipe 'bioconductor-dmrseq'

recipe bioconductor-dmrseq

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

Homepage:: https://bioconductor.org/packages/3.20/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:

1.30.0-0, 1.26.0-0, 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,

1.30.0-0, 1.26.0-0, 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:

on bioconductor-annotationhub >=4.0.0,<4.1.0
on bioconductor-annotatr >=1.36.0,<1.37.0
on bioconductor-biocparallel >=1.44.0,<1.45.0
on bioconductor-bsseq >=1.46.0,<1.47.0
on bioconductor-bumphunter >=1.52.0,<1.53.0
on bioconductor-delayedmatrixstats >=1.32.0,<1.33.0
on bioconductor-genomicranges >=1.62.0,<1.63.0
on bioconductor-iranges >=2.44.0,<2.45.0
on bioconductor-rtracklayer >=1.70.0,<1.71.0
on bioconductor-s4vectors >=0.48.0,<0.49.0
on bioconductor-seqinfo >=1.0.0,<1.1.0
on r-base >=4.5,<4.6.0a0
on r-ggplot2
on r-locfit
on r-matrixstats
on r-nlme
on r-outliers
on r-rcolorbrewer

Additional platforms:

Installation¶

You need a conda-compatible package manager (currently either pixi, conda, or micromamba) and the Bioconda channel already activated (see Usage). Below, we show how to install with either pixi or conda (for micromamba and mamba, commands are essentially the same as with conda).

Pixi¶

With pixi installed and the Bioconda channel set up (see Usage), to install globally, run:

pixi global install bioconductor-dmrseq

to add into an existing workspace instead, run:

pixi add bioconductor-dmrseq

In the latter case, make sure to first add bioconda and conda-forge to the channels considered by the workspace:

pixi workspace channel add conda-forge
pixi workspace channel add bioconda

Conda¶

With conda installed and the Bioconda channel set up (see Usage), to install into an existing and activated environment, run:

conda install bioconductor-dmrseq

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-dmrseq

with envname being the name of the desired environment.

Container¶

Alternatively, every Bioconda package is available as a container image for usage with your preferred container runtime. For e.g. docker, run:

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

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

Integrated deployment¶

Finally, note that many scientific workflow management systems directly integrate both conda and container based software deployment. Thus, workflow steps can be often directly annotated to use the package, leading to automatic deployment by the respective workflow management system, thereby improving reproducibility and transparency. Check the documentation of your workflow management system to find out about the integration.

Download stats¶

Link to this page¶

Render an badge with the following MarkDown:

[![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/bioconductor-dmrseq/README.html)