recipe bioconductor-hiccompare

HiCcompare: Joint normalization and comparative analysis of multiple Hi-C datasets







biotools: HiCcompare, doi: 10.1186/s12859-018-2288-x

HiCcompare provides functions for joint normalization and difference detection in multiple Hi-C datasets. HiCcompare operates on processed Hi-C data in the form of chromosome-specific chromatin interaction matrices. It accepts three-column tab-separated text files storing chromatin interaction matrices in a sparse matrix format which are available from several sources. HiCcompare is designed to give the user the ability to perform a comparative analysis on the 3-Dimensional structure of the genomes of cells in different biological states.`HiCcompare` differs from other packages that attempt to compare Hi-C data in that it works on processed data in chromatin interaction matrix format instead of pre-processed sequencing data. In addition, `HiCcompare` provides a non-parametric method for the joint normalization and removal of biases between two Hi-C datasets for the purpose of comparative analysis. `HiCcompare` also provides a simple yet robust method for detecting differences between Hi-C datasets.

package bioconductor-hiccompare

(downloads) docker_bioconductor-hiccompare



depends bioconductor-biocparallel:


depends bioconductor-genomicranges:


depends bioconductor-interactionset:


depends bioconductor-iranges:


depends bioconductor-rhdf5:


depends bioconductor-s4vectors:


depends r-base:


depends r-data.table:

depends r-dplyr:

depends r-ggplot2:

depends r-gridextra:

depends r-gtools:

depends r-kernsmooth:

depends r-mgcv:

depends r-pheatmap:



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-hiccompare

and update with::

   mamba update bioconductor-hiccompare

To create a new environment, run:

mamba create --name myenvname bioconductor-hiccompare

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<tag>

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

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