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Very low depth whole genome sequencing in complex trait association studies

Gilly, A; Southam, L; Suveges, D; Kuchenbaecker, K; Moore, R; Melloni, GEM; Hatzikotoulas, K; ... Zeggini, E; + view all (2018) Very low depth whole genome sequencing in complex trait association studies. Bioinformatics 10.1093/bioinformatics/bty1032. (In press). Green open access

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Abstract

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. Availability: 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/wtsiteam144/ transformPhenotype. Supplementary information: Supplementary data are available at Bioinformatics online.

Type: Article
Title: Very low depth whole genome sequencing in complex trait association studies
Open access status: An open access version is available from UCL Discovery
DOI: 10.1093/bioinformatics/bty1032
Publisher version: https://doi.org/10.1093/bioinformatics/bty1032
Language: English
Additional information: Copyright © The Author(s) 2018. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Division of Psychiatry
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Cardiovascular Science
URI: https://discovery.ucl.ac.uk/id/eprint/10066014
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