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
Journal BMC Bioinformatics
Year 2026
DOI
10.1093/bioinformatics/btag562
URL
https://doi.org/10.1093/bioinformatics/btag562
Keywords Keywords not found

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