4.5 Article

Evaluation of a whole-exome sequencing pipeline and benchmarking of causal germline variant prioritizers

期刊

HUMAN MUTATION
卷 43, 期 12, 页码 2010-2020

出版社

WILEY-HINDAWI
DOI: 10.1002/humu.24459

关键词

benchmarking; bioinformatics; germline; variant prioritization; whole-exome sequencing

资金

  1. Cabildo Insular de Tenerife [CGIEU0000219140]
  2. Agencia Canaria de Investigacion, Innovacion y Sociedad de la Informacion (ACIISI) [TESIS2020010002]
  3. Instituto Tecnologico y de Energias Renovables (ITER) [OA17/008]
  4. Ministerio de Ciencia e Innovacion [RTC-2017-6471-1]
  5. Instituto de Salud Carlos III [FI18/00230, CD19/00231, PI20/00876]

向作者/读者索取更多资源

This study assessed the performance of different tools in prioritizing germline causal variants in whole-exome sequencing (WES) data. Exomiser performed best in the top first rankings, while LIRICAL led in the top fifth rankings. Xrare had the highest diagnostic yield based on the more conservative top 10th rankings.
Most causal variants of Mendelian diseases are exonic. Whole-exome sequencing (WES) has become the diagnostic gold standard, but causative variant prioritization constitutes a bottleneck. Here we assessed an in-house sample-to-sequence pipeline and benchmarked free prioritization tools for germline causal variants from WES data. WES of 61 unselected patients with a known genetic disease cause was obtained. Variant prioritizations were performed by diverse tools and recorded to obtain a diagnostic yield when the causal variant was present in the first, fifth, and 10th top rankings. A fraction of causal variants was not captured by WES (8.2%) or did not pass the quality control criteria (13.1%). Most of the applications inspected were unavailable or had technical limitations, leaving nine tools for complete evaluation. Exomiser performed best in the top first rankings, while LIRICAL led in the top fifth rankings. Based on the more conservative top 10th rankings, Xrare had the highest diagnostic yield, followed by a three-way tie among Exomiser, LIRICAL, and PhenIX, then followed by AMELIE, TAPES, Phen-Gen, AIVar, and VarNote-PAT. Xrare, Exomiser, LIRICAL, and PhenIX are the most efficient options for variant prioritization in real patient WES data.

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