recipe bioconductor-multihiccompare

multiHiCcompare provides functions for joint normalization and difference detection in multiple Hi-C datasets. This extension of the original HiCcompare package now allows for Hi-C experiments with more than 2 groups and multiple samples per group. multiHiCcompare operates on processed Hi-C data in the form of sparse upper triangular matrices. It accepts four column (chromosome, region1, region2, IF) tab-separated text files storing chromatin interaction matrices. multiHiCcompare provides cyclic loess and fast loess (fastlo) methods adapted to jointly normalizing Hi-C data. Additionally, it provides a general linear model (GLM) framework adapting the edgeR package to detect differences in Hi-C data in a distance dependent manner.

Homepage

https://bioconductor.org/packages/3.9/bioc/html/multiHiCcompare.html

License

MIT + file LICENSE

Recipe

/bioconductor-multihiccompare/meta.yaml

package bioconductor-multihiccompare

(downloads) docker_bioconductor-multihiccompare

Versions

1.0.0-1, 1.0.0-0

Depends bioconductor-biocparallel

>=1.16.0,<1.17.0

Depends bioconductor-blma

>=1.6.0,<1.7.0

Depends bioconductor-edger

>=3.24.0,<3.25.0

Depends bioconductor-genomeinfodb

>=1.18.0,<1.19.0

Depends bioconductor-genomeinfodbdata

>=1.2.0,<1.3.0

Depends bioconductor-genomicranges

>=1.34.0,<1.35.0

Depends bioconductor-hiccompare

>=1.4.0,<1.5.0

Depends r-base

>=3.5.1,<3.5.2.0a0

Depends r-data.table

Depends r-dplyr

Depends r-metap

Depends r-pbapply

Depends r-pheatmap

Depends r-qqman

Requirements

Installation

With an activated Bioconda channel (see 2. Set up channels), install with:

conda install bioconductor-multihiccompare

and update with:

conda update bioconductor-multihiccompare

or use the docker container:

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

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