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Gilly, A. ; Southam, L.* ; Suveges, D.* ; Kuchenbaecker, K.* ; Moore, R.* ; Melloni, G.E.M.* ; Hatzikotoulas, K. ; Farmaki, A.E.* ; Ritchie, G.* ; Schwartzentruber, J.* ; Danecek, P.* ; Kilian, B.* ; Pollard, M.O.* ; Ge, X.* ; Tsafantakis, E.* ; Dedoussis, G.* ; Zeggini, E.

Very low-depth whole-genome sequencing in complex trait association studies.

Bioinformatics 35, 2555-2561 (2019)
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Open Access Green möglich sobald Postprint bei der ZB eingereicht worden ist.
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 characterization 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 1239 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 (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 140844 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.Availability and implementation The HELIC genotype and WGS datasets have been deposited to the European Genome-phenome Archive (https://www.ebi.ac.uk/ega/home): EGAD00010000518; EGAD00010000522; EGAD00010000610; EGAD00001001636, EGAD00001001637. The peakplotter software is available at https://github.com/wtsi-team144/peakplotter, the transformPhenotype app can be downloaded at https://github.com/wtsi-team144/transformPhenotype.Supplementary informationSupplementary data are available at Bioinformatics online.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Genotype Imputation; Variants
ISSN (print) / ISBN 1367-4803
Zeitschrift Bioinformatics
Quellenangaben Band: 35, Heft: 15, Seiten: 2555-2561 Artikelnummer: , Supplement: ,
Verlag Oxford University Press
Verlagsort Oxford
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Translational Genomics (ITG)