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RICOPILI: Rapid Imputation for COnsortias PIpeLIne

Open access

Lam, Max, Awasthi, Swapnil, Watson, Hunna J, Goldstein, Jackie, Panagiotaropoulou, Georgia, Trubetskoy, Vassily, Karlsson, Robert, Frei, Oleksander, Fan, Chun-Chieh, De Witte, Ward, Mota, Nina R, Mullins, Niamh, Brügger, Kim, Lee, S Hong, Wray, Naomi R, Skarabis, Nora, Huang, Hailiang, Neale, Benjamin, Daly, Mark J, Mattheisen, Manuel, Walters, Raymond, Ripke, Stephan·2020·Bioinformatics

DOI 10.1093/bioinformatics/btz633PMC PMC7868045

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Abstract

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, RICOPILI leverages on automated parallelization and cluster job management approaches for rapid production of imputed genome-wide data. A comprehensive meta-analysis of simulated GWAS data has been incorporated demonstrating each step of the pipeline. This includes all the associated visualization plots, to allow ease of data interpretation and manuscript preparation. Simulated GWAS datasets are also packaged with the pipeline for user training tutorials and developer work. Availability and implementation: RICOPILI has a flexible architecture to allow for ongoing development and incorporation of newer available algorithms and is adaptable to various HPC environments (QSUB, BSUB, SLURM and others). Specific links for genomic resources are either directly provided in this paper or via tutorials and external links. The central location hosting scripts and tutorials is found at this URL: https://sites.google.com/a/broadinstitute.org/RICOPILI/home Supplementary information: Supplementary data are available at Bioinformatics online.

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Authors: Lam, M., Awasthi, S., Watson, H. J., Goldstein, J., Panagiotaropoulou, G., Trubetskoy, V., Karlsson, R., Frei, O., Fan, C.-C., De Witte, W., Mota, N. R., Mullins, N., Brügger, K., Lee, S. H., Wray, N. R., Skarabis, N., Huang, H., Neale, B., Daly, M. J., Mattheisen, M., Walters, R., & Ripke, S.
Affiliations: Broad Institute (US)
University of North Carolina at Chapel Hill (US)
Karolinska Institutet (SE)
University of Oslo (NO)
Department of Human Genetics, Donders Institute for Brain , Cognition and Behaviour
Radboud University Nijmegen (NL)
Icahn School of Medicine at Mount Sinai (US)
University of Bergen (NO)
University of South Australia (AU)
The University of Queensland (AU)
Charité – Universitätsmedizin Berlin (DE)
Aarhus University (DK)
Corresponding author: Ripke, Stephan
ORCID: Lam, Max
Awasthi, Swapnil
Watson, Hunna J
Panagiotaropoulou, Georgia
Trubetskoy, Vassily
Karlsson, Robert
Fan, Chun-Chieh
Mota, Nina R
Mullins, Niamh
Brügger, Kim
Lee, S Hong
Wray, Naomi R
Skarabis, Nora
Huang, Hailiang
Neale, Benjamin
Daly, Mark J
Mattheisen, Manuel
Walters, Raymond
Ripke, Stephan
Venue: Bioinformatics
Publisher: Oxford University Press (OUP)
Published: 2019-08-08
Volume: 36
Issue: 3
Pages: 930-933
ISSN: 1367-4803 (ISSN-L)
1367-4811
DOI: 10.1093/bioinformatics/btz633
PMC: PMC7868045
OpenAlex: W2967846176
Cited by: 315
References: 20
Citations by year: 2026: 39 · 2025: 49 · 2024: 56 · 2023: 57 · 2022: 47 · 2021: 36 · 2020: 23 · 2019: 7
FWCI: 17.01
Type: journal article
Language: en
Open access: hybrid
doi.org
Licence: cc-by-nc
creativecommons.org/licenses/by-nc/4.0/ (vor)
Locations: Bioinformatics (publishedVersion, cc-by-nc)
bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
PubMed Central (publishedVersion, cc-by-nc)
PubMed (publishedVersion)
Radboud Repository (Radboud University) (submittedVersion)
UWA Profiles and Research Repository (UWA) (submittedVersion, cc-by-nc)
UniSA Research Outputs Repository (University of South Australia) (submittedVersion, other-oa)
Adelaide Research & Scholarship (AR&S) (University of Adelaide) (submittedVersion, cc-by-nc)
NORA - Norwegian Open Research Archives (submittedVersion, cc-by-nc)
Radboud Repository (Radboud University) (submittedVersion, other-oa)
Funders: National Institutes of Health (U01 MH109528, U01 MH1095320)
National Medical Research Council (NMRC/TCR/003, MH095: 003/008-1014, NMRC/CG/004/2013, NMRC/SEEDFD/019/2017)
NIH/NIMH (U01MH109528)
Broad Institute of MIT and Harvard (691099)
German Research Foundation (RI2846/1-1)
NIH
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic and phenotypic traits in livestock
Keywords: genotype imputation, quality control, psychiatric genomics, polygenic risk scoring, replication analysis, meta-analysis, high-performance computing, parallelization, Perl
MeSH terms: Algorithms, Software, Genome, Genomics, Genome-Wide Association Study

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