map3C: a computational tool for processing multiomic single-cell Hi-C data

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ID: 323010
2026
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Abstract
SUMMARY: The emergence of multiomic single-cell Hi-C methods, which simultaneously profile chromatin conformation and other modalities such as gene expression or DNA methylation, creates tremendous opportunities for studying the genome's structure-function relationships. Existing tools for processing multiomic single-cell Hi-C datasets lack certain key functions for downstream bioinformatics analysis. We present map3C, a software tool that incorporates additional key functions. Specifically, we demonstrate that map3C facilitates multiomic scHi-C processing, quality control, and identification of structural variant locations in the genome. AVAILABILITY AND IMPLEMENTATION: map3C is available at https://github.com/luogenomics/map3C and is archived at https://doi.org/10.5281/zenodo.20724719. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Reference Key
openalex_W4415210245 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Joseph Galasso, Ye Wang, Frank Alber, Jason Ernst, Chongyuan Luo
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Journal BMC Bioinformatics
Year 2026
DOI
10.1093/bioinformatics/btag562
URL
https://doi.org/10.1093/bioinformatics/btag562
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