RICOPILI: Rapid Imputation for COnsortias PIpeLIne

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

  • Max Lam, Broad Institute, Massachusetts General Hospital, Boston, Zucker Hillside Hospital, Institute of Mental Health, Agency for Science, Technology and Research
  • ,
  • Swapnil Awasthi, Broad Institute, Charité – Universitätsmedizin Berlin
  • ,
  • Hunna J. Watson, 1] The Bioinformatics Centre, Department of Biology & Biotech Research and Innovation Centre, University of Copenhagen, Ole Maaloes Vej 5, DK-2200 Copenhagen, Denmark [2] Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina 27599, USA., University of Western Australia, Curtin University
  • ,
  • Jackie Goldstein, Broad Institute, Massachusetts General Hospital, Boston
  • ,
  • Georgia Panagiotaropoulou, Broad Institute, Charité – Universitätsmedizin Berlin
  • ,
  • Vassily Trubetskoy, Broad Institute, Charité – Universitätsmedizin Berlin
  • ,
  • Robert Karlsson, Karolinska Institutet
  • ,
  • Oleksander Frei, Universitetet i Oslo
  • ,
  • Chun Chieh Fan, Universitetet i Oslo
  • ,
  • Ward De Witte, Donders Institute for Brain
  • ,
  • Nina R. Mota, Donders Institute for Brain, Radboud University Nijmegen Medical Centre
  • ,
  • Niamh Mullins, Icahn School of Medicine at Mount Sinai
  • ,
  • Kim Brügger, University of Bergen
  • ,
  • S. Hong Lee, University of South Australia
  • ,
  • Naomi R. Wray, The University of Queensland
  • ,
  • Nora Skarabis, Charité – Universitätsmedizin Berlin
  • ,
  • Hailiang Huang, Broad Institute, Massachusetts General Hospital, Boston
  • ,
  • Benjamin Neale, Broad Institute, Massachusetts General Hospital, Boston
  • ,
  • Mark J. Daly, Broad Institute, Massachusetts General Hospital, Boston
  • ,
  • Manuel Mattheisen
  • Raymond Walters, Broad Institute, Massachusetts General Hospital, Boston
  • ,
  • Stephan Ripke, Broad Institute, Massachusetts General Hospital, Boston, Charité – Universitätsmedizin Berlin

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.

Original languageEnglish
JournalBioinformatics (Oxford, England)
Volume36
Issue3
Pages (from-to)930-933
Number of pages4
ISSN1367-4803
DOIs
Publication statusPublished - 2020

See relations at Aarhus University Citationformats

ID: 182530593