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Identifying crossovers and shared genetic material in whole genome sequencing data from families.
Paskov, Kelley; Chrisman, Brianna; Stockham, Nathaniel; Washington, Peter Yigitcan; Dunlap, Kaitlyn; Jung, Jae-Yoon; Wall, Dennis P.
Affiliation
  • Paskov K; Department of Biomedical Data Science, Stanford University, Stanford, California 94305, USA; kpaskov@stanford.edu.
  • Chrisman B; Department of Bioengineering, Stanford University, Stanford, California 94305, USA.
  • Stockham N; Department of Neuroscience, Stanford University, Stanford, California 94305, USA.
  • Washington PY; Department of Bioengineering, Stanford University, Stanford, California 94305, USA.
  • Dunlap K; Department of Biomedical Data Science, Stanford University, Stanford, California 94305, USA.
  • Jung JY; Department of Pediatrics, Stanford University, Stanford, California 94305, USA.
  • Wall DP; Department of Biomedical Data Science, Stanford University, Stanford, California 94305, USA.
Genome Res ; 33(10): 1747-1756, 2023 10.
Article in En | MEDLINE | ID: mdl-37879861
Large, whole-genome sequencing (WGS) data sets containing families provide an important opportunity to identify crossovers and shared genetic material in siblings. However, the high variant calling error rates of WGS in some areas of the genome can result in spurious crossover calls, and the special inheritance status of the X Chromosome presents challenges. We have developed a hidden Markov model that addresses these issues by modeling the inheritance of variants in families in the presence of error-prone regions and inherited deletions. We call our method PhasingFamilies. We validate PhasingFamilies using the platinum genome family NA1281 (precision: 0.81; recall: 0.97), as well as simulated genomes with known crossover positions (precision: 0.93; recall: 0.92). Using 1925 quads from the Simons Simplex Collection, we found that PhasingFamilies resolves crossovers to a median resolution of 3527.5 bp. These crossovers recapitulate existing recombination rate maps, including for the X Chromosome; produce sibling pair IBD that matches expected distributions; and are validated by the haplotype estimation tool SHAPEIT. We provide an efficient, open-source implementation of PhasingFamilies that can be used to identify crossovers from family sequencing data.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Genome / Inheritance Patterns Limits: Humans Language: En Journal: Genome Res Journal subject: BIOLOGIA MOLECULAR / GENETICA Year: 2023 Document type: Article Country of publication: Estados Unidos

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Genome / Inheritance Patterns Limits: Humans Language: En Journal: Genome Res Journal subject: BIOLOGIA MOLECULAR / GENETICA Year: 2023 Document type: Article Country of publication: Estados Unidos