Very low depth whole genome sequencing in complex trait association studies
By
Arthur Gilly,
Lorraine Southam,
Daniel Suveges,
Karoline Kuchenbaecker,
Rachel Moore,
Giorgio Melloni,
Konstantinos Hatzikotoulas,
Aliki-Eleni Farmaki,
Graham Ritchie,
Jeremy Schwartzentruber,
Petr Danecek,
Britt Kilian,
Martin Pollard,
Xiangyu Ge,
Emmanouil Tsafantakis,
George V. Dedoussis,
Eleftheria Zeggini
Posted 28 Jul 2017
bioRxiv DOI: 10.1101/169789
(published DOI: 10.1093/bioinformatics/bty1032)
Motivation: Very low depth sequencing has been proposed as a cost-effective approach to capture low-frequency and rare variation in complex trait association studies. However, a full characterisation of the genotype quality and association power for very low depth sequencing designs is still lacking. Results: We perform cohort-wide whole genome sequencing (WGS) at low depth in 1,239 individuals (990 at 1x depth and 249 at 4x depth) from an isolated population, and establish a robust pipeline for calling and imputing very low depth WGS genotypes from standard bioinformatics tools. Using genotyping chip, whole-exome sequencing (WES, 75x depth) and high-depth (22x) WGS data in the same samples, we examine in detail the sensitivity of this approach, and show that imputed 1x WGS recapitulates 95.2% of variants found by imputed GWAS with an average minor allele concordance of 97% for common and low-frequency variants. In our study, 1x further allowed the discovery of 140,844 true low-frequency variants with 73% genotype concordance when compared to high-depth WGS data. Finally, using association results for 57 quantitative traits, we show that very low depth WGS is an efficient alternative to imputed GWAS chip designs, allowing the discovery of up to twice as many true association signals than the classical imputed GWAS design.
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