March 1, 2024Open Access

NPSV-deep: a deep learning method for genotyping structural variants in short read genome sequencing data

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Abstract

Structural variants (SVs) play a causal role in numerous diseases but can be difficult to detect and accurately genotype (determine zygosity) with short-read genome sequencing data (SRS). Improving SV genotyping accuracy in SRS data, particularly for the many SVs first detected with long-read sequencing, will improve our understanding of genetic variation.

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Linderman et al. (Fri,) studied this question.

synapsesocial.com/papers/68e7634db6db6435876d9536 https://doi.org/https://doi.org/10.1093/bioinformatics/btae129

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1Characterizing the Major Structural Variant Alleles of the Human Genome2019 · 577 citations
2GINDEL: Accurate Genotype Calling of Insertions and Deletions from Low Coverage Population Sequence Reads2014 · 27 citations
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4svviz: a read viewer for validating structural variants2015 · 61 citations
5A reference data set of 5.4 million phased human variants validated by genetic inheritance from sequencing a three-generation 17-member pedigree2016 · 424 citations

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