Linked-read analysis identifies mutations in single-cell DNA-sequencing data.
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ABSTRACT:
SUBMITTER: Bohrson CL
PROVIDER: S-EPMC6900933 | biostudies-literature | 2019 Apr
REPOSITORIES: biostudies-literature
Publications
Linked-read analysis identifies mutations in single-cell DNA-sequencing data.
Bohrson Craig L CL Barton Alison R AR Lodato Michael A MA Rodin Rachel E RE Luquette Lovelace J LJ Viswanadham Vinay V VV Gulhan Doga C DC Cortés-Ciriano Isidro I Sherman Maxwell A MA Kwon Minseok M Coulter Michael E ME Galor Alon A Walsh Christopher A CA Park Peter J PJ
Nature genetics 20190318 4
Whole-genome sequencing of DNA from single cells has the potential to reshape our understanding of mutational heterogeneity in normal and diseased tissues. However, a major difficulty is distinguishing amplification artifacts from biologically derived somatic mutations. Here, we describe linked-read analysis (LiRA), a method that accurately identifies somatic single-nucleotide variants (sSNVs) by using read-level phasing with nearby germline heterozygous polymorphisms, thereby enabling the chara ...[more]
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