map3C: a computational tool for processing multiomic single-cell Hi-C data
Abstract
SUMMARY: The emergence of multiomic single-cell Hi-C (scHi-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 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. AVAILABILITY AND IMPLEMENTATION: map3C is available at https://github.com/luogenomics/map3C and is archived at https://doi.org/10.5281/zenodo.20724719.
Fields of Study & Subjects
Single-cell and spatial transcriptomics
Publication details
- Journal / source
- Bioinformatics
- Volume
- 42
- Issue
- 8
- Publication date
- 29 July 2026
- Language
- EN