{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Sanders AD"],"funding":["European Research Council","NHGRI NIH HHS"],"pagination":["343-354"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC7612647"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["38(3)"],"pubmed_abstract":["Structural variation (SV), involving deletions, duplications, inversions and translocations of DNA segments, is a major source of genetic variability in somatic cells and can dysregulate cancer-related pathways. However, discovering somatic SVs in single cells has been challenging, with copy-number-neutral and complex variants typically escaping detection. Here we describe single-cell tri-channel processing (scTRIP), a computational framework that integrates read depth, template strand and haplotype phase to comprehensively discover SVs in individual cells. We surveyed SV landscapes of 565 single cells, including transformed epithelial cells and patient-derived leukemic samples, to discover abundant SV classes, including inversions, translocations and complex DNA rearrangements. Analysis o"],"journal":["Nature biotechnology"],"pubmed_title":["Single-cell analysis of structural variations and complex rearrangements with tri-channel processing."],"pmcid":["PMC7612647"],"funding_grant_id":["336045","773026","U41 HG007497"],"pubmed_authors":["Ghareghani M","Rausch T","Schrappe M","Kunz JB","Sanders AD","Jeong H","Porubsky D","Kinanen V","Meiers S","Jenni S","Mardin BR","Zimmermann J","van Vliet MACC","Bourquin JP","Bolognini D","Kulozik AE","Marschall T","Raeder B","Bornhauser B","Korbel JO","Richter-Pechanska P","Benes V","Longo GMC"],"additional_accession":[]},"is_claimable":false,"name":"Single-cell analysis of structural variations and complex rearrangements with tri-channel processing.","description":"Structural variation (SV), involving deletions, duplications, inversions and translocations of DNA segments, is a major source of genetic variability in somatic cells and can dysregulate cancer-related pathways. However, discovering somatic SVs in single cells has been challenging, with copy-number-neutral and complex variants typically escaping detection. Here we describe single-cell tri-channel processing (scTRIP), a computational framework that integrates read depth, template strand and haplotype phase to comprehensively discover SVs in individual cells. We surveyed SV landscapes of 565 single cells, including transformed epithelial cells and patient-derived leukemic samples, to discover abundant SV classes, including inversions, translocations and complex DNA rearrangements. Analysis o","dates":{"release":"2020-01-01T00:00:00Z","publication":"2020 Mar","modification":"2025-04-04T02:24:18.1Z","creation":"2025-04-04T02:24:18.1Z"},"accession":"S-EPMC7612647","cross_references":{"pubmed":["31873213"],"doi":["10.1038/s41587-019-0366-x"]}}