作者
Max Lam, Swapnil Awasthi, Hunna J Watson, Jackie Goldstein, Georgia Panagiotaropoulou, Vassily Trubetskoy, Robert Karlsson, Oleksander Frei, Chun-Chieh Fan, Ward De Witte, Nina R Mota, Niamh Mullins, Kim Brügger, S Hong Lee, Naomi R Wray, Nora Skarabis, Hailiang Huang, Benjamin Neale, Mark J Daly, Manuel Mattheisen, Raymond Walters, Stephan Ripke
发表日期
2020/2/1
期刊
Bioinformatics
卷号
36
期号
3
页码范围
930-933
出版商
Oxford University Press
简介
Summary
Genome-wide association study (GWAS) analyses, at sufficient sample sizes and power, have successfully revealed biological insights for several complex traits. RICOPILI, an open-sourced Perl-based pipeline was developed to address the challenges of rapidly processing large-scale multi-cohort GWAS studies including quality control (QC), imputation and downstream analyses. The pipeline is computationally efficient with portability to a wide range of high-performance computing environments. RICOPILI was created as the Psychiatric Genomics Consortium pipeline for GWAS and adopted by other users. The pipeline features (i) technical and genomic QC in case-control and trio cohorts, (ii) genome-wide phasing and imputation, (iv) association analysis, (v) meta-analysis, (vi) polygenic risk scoring and (vii) replication analysis. Notably, a major differentiator from other GWAS pipelines …
引用总数
20192020202120222023202482252797437
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