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NPSV: A simulation-driven approach to genotyping structural variants in whole-genome sequencing data
Author(s) -
Michael D. Linderman,
Crystal Paudyal,
Musab Shakeel,
William L. Kelley,
Ali Bashir,
Bruce D. Gelb
Publication year - 2021
Publication title -
gigascience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.947
H-Index - 54
ISSN - 2047-217X
DOI - 10.1093/gigascience/giab046
Subject(s) - genotyping , computational biology , genome , computer science , whole genome sequencing , data science , biology , genetics , genotype , gene
Structural variants (SVs) play a causal role in numerous diseases but are difficult to detect and accurately genotype (determine zygosity) in whole-genome next-generation sequencing data. SV genotypers that assume that the aligned sequencing data uniformly reflect the underlying SV or use existing SV call sets as training data can only partially account for variant and sample-specific biases.

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