A flexible pipeline for reproducible exome-wide rare variant gene-trait associations

Abstract Summary Exome-wide gene-burden association studies are widely used to assess gene – trait relationships. By focusing on coding variants, such analyses can directly quantify the magnitude and direction of a gene’s effect on a given trait across the proteome, information that cannot be easily derived from genome-wide associate studies. However, the lack of a standardized workflow poses a significant challenge for reproducibility. Here, we provide a customizable workflow implemented in Python 3 and Nextflow for performing exome-wide rare variant gene – trait association testing. We demonstrated its utility by replicating three recent studies. This workflow will also serve as a framework for performing similar analyses in a standardized and systematic manner. Availability and Implementation This workflow is publicly available at https://github.com/richardslab/EXWAS_pipeline under the MIT license. Supplementary information Supplementary information will be made available online. Competing Interest Statement JBR has served as an advisor to GlaxoSmithKline and Deerfield Capital. JBR is the CEO of 5 Prime Sciences. YC is an employee of 5 Prime Sciences. No conflict of interests is declared for the other authors. Funding Statement The Richards research group is supported by the Canadian Institutes of Health Research (CIHR: 365825; 409511, 100558), the Lady Davis Institute of the Jewish General Hospital, the Canadian Foundation for Innovation, the NIH Foundation, Cancer Research UK, Genome Quebec, the Public Health Agency of Canada, Genome Quebec, McGill University and the Fonds de Recherche Queebec Sante (FRQS). JBR is supported by a FRQS Clinical Research Scholarship. Support from Calcul Quebec and Compute Canada is acknowledged. This work was supported by Cancer Research UK [grant umber C18281/A29019]. TwinsUK is funded by the Welcome Trust, Medical Research Council, European Union, the National Institute for Health Research (NIHR)-funded BioResource, Clinical Research Facility and Biomedical Research Centre based at Guy's and St Thomas' NHS Foundation Trust in partnership with King's College London. KYHL was supported by CIHR doctoral scholarship. These funding agencies had no role in the design, implementation or interpretation of this study. Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Data Availability The configuration files for each replication study are provided on the GitHub repository (https://github.com/richardslab/EXWAS_pipeline). ExWAS results from Backman et al, Zhao et al, and Chen et al can be obtained from GWAS catalog or the original publication.