Journal article
Accurate genotyping across variant classes and lengths using variant graphs
University of Copenhagen1
University of Oslo2
University of Bergen3
University of North Carolina at Chapel Hill4
Genomic Epidemiology, Department of Bio and Health Informatics, Technical University of Denmark5
Karolinska Institutet6
Disease Intelligence and Molecular Evolution, Department of Bio and Health Informatics, Technical University of Denmark7
Aarhus University8
Department of Bio and Health Informatics, Technical University of Denmark9
Metagenomics, Department of Bio and Health Informatics, Technical University of Denmark10
Integrative Systems Biology, Department of Bio and Health Informatics, Technical University of Denmark11
South China University of Technology12
BGI Europe A/S13
BGI Group14
Technical University of Denmark15
...and 5 moreGenotype estimates from short-read sequencing data are typically based on the alignment of reads to a linear reference, but reads originating from more complex variants (for example, structural variants) often align poorly, resulting in biased genotype estimates. This bias can be mitigated by first collecting a set of candidate variants across discovery methods, individuals and databases, and then realigning the reads to the variants and reference simultaneously.
However, this realignment problem has proved computationally difficult. Here, we present a new method (BayesTyper) that uses exact alignment of read k-mers to a graph representation of the reference and variants to efficiently perform unbiased, probabilistic genotyping across the variation spectrum.
We demonstrate that BayesTyper generally provides superior variant sensitivity and genotyping accuracy relative to existing methods when used to integrate variants across discovery approaches and individuals. Finally, we demonstrate that including a ‘variation-prior’ database containing already known variants significantly improves sensitivity.
Language: | English |
---|---|
Publisher: | Nature Publishing Group US |
Year: | 2018 |
Pages: | 1054-1059 |
ISSN: | 15461718 and 10614036 |
Types: | Journal article |
DOI: | 10.1038/s41588-018-0145-5 |
ORCIDs: | Petersen, Bent , Gonzalez-Izarzugaza, Jose Maria , Lund, Ole , Gupta, Ramneek , Rasmussen, Simon , 0000-0002-5147-6282 , 0000-0001-8748-3831 , 0000-0003-4821-430X , 0000-0002-3321-3972 and 0000-0003-0316-5866 |