Article

SVLearn: a dual-reference machine learning approach enables accurate cross-species genotyping of structural variants

2024-09-12

Abstract excerpt

<title>Abstract</title> Structural variations (SVs) are diverse forms of genetic alterations and drive a wide range of human diseases. Accurately genotyping SVs, particularly occurring at repetitive genomic regions, from short-read sequencing data remains challenging. Here, we introduce SVLearn, a machine-learning approach for genotyping bi-allelic SVs. It exploits a dual-reference strategy to engineer a curat...

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Literature Corpus work: 485c4eba-3af1-5ac7-97e7-743fc32ee1cf
DOI: 10.21203/rs.3.rs-4945875/v1

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