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.
Useful links:
Maintainer: Maigné Élise elise.maigne@inrae.fr
Authors:
Kurylo Cyril cyril.kurylo@inrae.fr
Zytnicki Matthias matthias.zytnicki@inrae.fr
Foissac Sylvain sylvain.foissac@inrae.fr