PT  - JOURNAL ARTICLE
AU  - Sai Chen
AU  - Peter Krusche
AU  - Egor Dolzhenko
AU  - Rachel M. Sherman
AU  - Roman Petrovski
AU  - Felix Schlesinger
AU  - Melanie Kirsche
AU  - David R. Bentley
AU  - Michael C. Schatz
AU  - Fritz J. Sedlazeck
AU  - Michael A. Eberle
TI  - Paragraph: A graph-based structural variant genotyper for short-read sequence data
AID  - 10.1101/635011
DP  - 2019 Jan 01
TA  - bioRxiv
PG  - 635011
4099  - http://biorxiv.org/content/early/2019/09/24/635011.short
4100  - http://biorxiv.org/content/early/2019/09/24/635011.full
AB  - Accurate detection and genotyping of structural variations (SVs) from short-read data is a long-standing area of development in genomics research and clinical sequencing pipelines. We introduce Paragraph, an accurate genotyper that models SVs using sequence graphs and SV annotations. We demonstrate the accuracy of Paragraph on whole-genome sequence data from three samples using long read SV calls as the truth set, and then apply Paragraph at scale to a cohort of 100 short-read sequenced samples of diverse ancestry. Our analysis shows that Paragraph has better accuracy than other existing genotypers and can be applied to population-scale studies.SVstructural variationbpbase pairTRtandem repeat