recipe bioconductor-hicdoc

A/B compartment detection and differential analysis

Homepage:

https://bioconductor.org/packages/3.16/bioc/html/HiCDOC.html

License:

LGPL (>= 3)

Recipe:

/bioconductor-hicdoc/meta.yaml

HiCDOC normalizes intrachromosomal Hi-C matrices, uses unsupervised learning to predict A/B compartments from multiple replicates, and detects significant compartment changes between experiment conditions. It provides a collection of functions assembled into a pipeline to filter and normalize the data, predict the compartments and visualize the results. It accepts several type of data: tabular `.tsv` files, Cooler `.cool` or `.mcool` files, Juicer `.hic` files or HiC-Pro `.matrix` and `.bed` files.

package bioconductor-hicdoc

Versions:

1.0.0-0

Depends:

• bioconductor-biocgenerics >=0.44.0,<0.45.0

• bioconductor-biocparallel >=1.32.0,<1.33.0

• bioconductor-genomeinfodb >=1.34.0,<1.35.0

• bioconductor-genomicranges >=1.50.0,<1.51.0

• bioconductor-interactionset >=1.26.0,<1.27.0

• bioconductor-multihiccompare >=1.16.0,<1.17.0

• bioconductor-rhdf5 >=2.42.0,<2.43.0

• bioconductor-s4vectors >=0.36.0,<0.37.0

• bioconductor-summarizedexperiment >=1.28.0,<1.29.0

• bioconductor-zlibbioc >=1.44.0,<1.45.0

• libblas >=3.9.0,<4.0a0

• libgcc-ng >=12

• liblapack >=3.9.0,<4.0a0

• libstdcxx-ng >=12

• r-base >=4.2,<4.3.0a0

• r-data.table

• r-ggextra

• r-ggplot2

• r-ggpubr

• r-gridextra

• r-gtools

• r-pbapply

• r-rcpp >=0.12.8

Required By:

Installation

With an activated Bioconda channel (see set-up-channels), install with:

conda install bioconductor-hicdoc

and update with:

conda update bioconductor-hicdoc

or use the docker container:

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

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

Download stats

Link to this page

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