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Existing tools for processing multiomic scHi-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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>map3C is available at https:\/\/github.com\/luogenomics\/map3C and is archived at https:\/\/doi.org\/10.5281\/zenodo.20724719.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btag562","type":"journal-article","created":{"date-parts":[[2026,7,29]],"date-time":"2026-07-29T11:19:25Z","timestamp":1785323965000},"source":"Crossref","is-referenced-by-count":0,"title":["map3C: a computational tool for processing multiomic single-cell Hi-C 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