A flexible pipeline for reproducible exome-wide rare variant gene-trait associations
Liang, K. Y.; Kreuzer, E.; Ilboudo, Y.; Chen, Y.; Richards, J. B.; Butler-Laporte, G.
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SummaryExome-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 genes 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 ImplementationThis workflow is publicly available at https://github.com/richardslab/EXWAS_pipeline under the MIT license. Supplementary informationSupplementary information will be made available online.
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