runHiC

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runHiC is an easy-to-use command-line tool for Hi-C data processing.

Since version 0.8.6, runHiC has supported data from all kinds of 3C-based experiments, including Hi-C, Micro-C, HiChIP/PLAC-Seq, and ChIA-PET. For experiments that do not use restriction enzymes for DNA fragmentation, you can set the enzyme name arbitrarily for your record. For example, for Micro-C, you can set it to MNase; for ChIA-PET, you can set it to sonication.

Since version 0.8.5, runHiC has changed the default aligner to chromap <https://github.com/haowenz/chromap>, which is comparable to bwa-mem <https://github.com/lh3/bwa> in alignment accuracy, but runs over 10 times faster.

Since version 0.8.1, runHiC can be used directly on Arima HiC <https://arimagenomics.com>_ data by setting the enzyme name to Arima.

Since version 0.8.0, runHiC has changed its default data container/format from HDF5 to Pairs <https://github.com/4dn-dcic/pairix/blob/master/pairs_format_specification.md>_ and Cooler <https://github.com/mirnylab/cooler>_.

Design Concepts

runHiC is designed to process Hi-C data from raw sequencing reads(.sra, .fastq, .fastq.gz) to the ICE-corrected contact matrices. It currently contains 5 subcommands:

+------------+-------------------------------------------------------------------------------------------------------------------+ | mapping | Map raw sequencing reads to a supplied genome. Support three read aligners: chromap, bwa and minimap2. | +------------+-------------------------------------------------------------------------------------------------------------------+ | filtering | Perform read-level and fragment-level noise removing | +------------+-------------------------------------------------------------------------------------------------------------------+ | binning | 1.Generate contact matirx; 2. Perform ICE/matrix-balancing normalization | +------------+-------------------------------------------------------------------------------------------------------------------+ | pileup | Perform the entire processing steps from mapping to binning | +------------+-------------------------------------------------------------------------------------------------------------------+ | quality | Evaluate the quality of your Hi-C data | +------------+-------------------------------------------------------------------------------------------------------------------+

Links

• Detailed Documentation <http://xiaotaowang.github.io/HiC_pipeline/>_
  • Installation <http://xiaotaowang.github.io/HiC_pipeline/install.html>_
  • Quick Start <http://xiaotaowang.github.io/HiC_pipeline/quickstart.html>_
  • Data Quality <http://xiaotaowang.github.io/HiC_pipeline/quality.html>_
  • Parallel Computation <http://xiaotaowang.github.io/HiC_pipeline/parallel.html>_
• Code Repository <https://github.com/XiaoTaoWang/HiC_pipeline/>_ (At GitHub, Track the package issue)
• PyPI <https://pypi.python.org/pypi/runHiC>_ (Download and Installation)

Usage

Open a terminal, type runHiC -h or runHiC <subcommand> -h for help information.

Citation

Xiaotao Wang. (2016). runHiC: A user-friendly Hi-C data processing software based on hiclib. Zenodo. 10.5281/zenodo.55324 <http://dx.doi.org/10.5281/zenodo.55324>_