{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Zheng J"],"funding":["Fundamental Research Funds for the Central Universities","Sun Yat-sen University","National Natural Science Foundation of China","Natural Science Foundation of Guangdong Province"],"pagination":["bbad379"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC10691963"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["25(1)"],"pubmed_abstract":["Single-cell Hi-C (scHi-C) technology enables the investigation of 3D chromatin structure variability across individual cells. However, the analysis of scHi-C data is challenged by a large number of missing values. Here, we present a scHi-C data imputation model HiC-SGL, based on Subgraph extraction and graph representation learning. HiC-SGL can also learn informative low-dimensional embeddings of cells. We demonstrate that our method surpasses existing methods in terms of imputation accuracy and clustering performance by various metrics."],"journal":["Briefings in bioinformatics"],"pubmed_title":["Subgraph extraction and graph representation learning for single cell Hi-C imputation and clustering."],"pmcid":["PMC10691963"],"funding_grant_id":["2023A1515011907","23xkjc003","61872395","92249303"],"pubmed_authors":["Zheng J","Yang Y","Dai Z"],"additional_accession":[]},"is_claimable":false,"name":"Subgraph extraction and graph representation learning for single cell Hi-C imputation and clustering.","description":"Single-cell Hi-C (scHi-C) technology enables the investigation of 3D chromatin structure variability across individual cells. However, the analysis of scHi-C data is challenged by a large number of missing values. Here, we present a scHi-C data imputation model HiC-SGL, based on Subgraph extraction and graph representation learning. HiC-SGL can also learn informative low-dimensional embeddings of cells. We demonstrate that our method surpasses existing methods in terms of imputation accuracy and clustering performance by various metrics.","dates":{"release":"2023-01-01T00:00:00Z","publication":"2023 Nov","modification":"2026-05-28T21:34:57.22Z","creation":"2025-04-19T20:22:07.822Z"},"accession":"S-EPMC10691963","cross_references":{"pubmed":["38040494"],"doi":["10.1093/bib/bbad379"]}}