recipe bioconductor-atacseqqc

ATAC-seq Quality Control

Homepage:

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

License:

GPL (>= 2)

Recipe:

/bioconductor-atacseqqc/meta.yaml

ATAC-seq, an assay for Transposase-Accessible Chromatin using sequencing, is a rapid and sensitive method for chromatin accessibility analysis. It was developed as an alternative method to MNase-seq, FAIRE-seq and DNAse-seq. Comparing to the other methods, ATAC-seq requires less amount of the biological samples and time to process. In the process of analyzing several ATAC-seq dataset produced in our labs, we learned some of the unique aspects of the quality assessment for ATAC-seq data.To help users to quickly assess whether their ATAC-seq experiment is successful, we developed ATACseqQC package partially following the guideline published in Nature Method 2013 (Greenleaf et al.), including diagnostic plot of fragment size distribution, proportion of mitochondria reads, nucleosome positioning pattern, and CTCF or other Transcript Factor footprints.

package bioconductor-atacseqqc

versions:

1.26.0-0,  1.24.0-0,  1.22.0-0,  1.18.0-0,  1.16.0-0,  1.14.4-1,  1.14.4-0,  1.14.0-0,  1.12.0-0, 

1.26.0-0,  1.24.0-0,  1.22.0-0,  1.18.0-0,  1.16.0-0,  1.14.4-1,  1.14.4-0,  1.14.0-0,  1.12.0-0,  1.10.0-0,  1.8.5-0,  1.6.4-0,  1.4.3-0,  1.2.0-0,  1.0.5-0

depends bioconductor-biocgenerics:

>=0.48.0,<0.49.0

depends bioconductor-biostrings:

>=2.70.0,<2.71.0

depends bioconductor-bsgenome:

>=1.70.0,<1.71.0

depends bioconductor-chippeakanno:

>=3.36.0,<3.37.0

depends bioconductor-edger:

>=4.0.0,<4.1.0

depends bioconductor-genomeinfodb:

>=1.38.0,<1.39.0

depends bioconductor-genomicalignments:

>=1.38.0,<1.39.0

depends bioconductor-genomicranges:

>=1.54.0,<1.55.0

depends bioconductor-genomicscores:

>=2.14.0,<2.15.0

depends bioconductor-iranges:

>=2.36.0,<2.37.0

depends bioconductor-limma:

>=3.58.0,<3.59.0

depends bioconductor-motifstack:

>=1.46.0,<1.47.0

depends bioconductor-rsamtools:

>=2.18.0,<2.19.0

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-kernsmooth:

depends r-preseqr:

depends r-randomforest:

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-atacseqqc

and update with::

   mamba update bioconductor-atacseqqc

To create a new environment, run:

mamba create --name myenvname bioconductor-atacseqqc

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-atacseqqc:<tag>

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

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-atacseqqc/README.html)