drugMR: A multi-omics pipeline for genetically anchored drug-target discovery
Comesana Cimadevila, G.; Dib, M.-J.; Bracher-Smith, M.; Ducotterd, F.; Salih, D. A.; Bray, N. J.; Simmonds, E.; Escott-Price, V.
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Motivation: Genetically supported drug targets are an estimated 2.6 times more likely to succeed clinically, yet a disease association alone does not show which protein to target, in which direction, or what other effects may follow. This currently requires chaining separate tools. Results: drugMR is a Nextflow pipeline that, from GWAS and pQTL summary statistics, runs cis-Mendelian randomisation, colocalisation, SMR-HEIDI with bulk and/or single-cell QTLs, three-trait colocalisation and a phenome-wide screen for adverse effects and repurposing. Datasets are added through a manifest, every step runs in containers on a laptop, cluster or cloud, and results are explored in a dashboard. Applied to schizophrenia with brain pQTLs, drugMR tested 2,019 proteins in 4 h 19 min and prioritised 58 proteogenomic targets, 22 with multi-omic support; 4 had potential adverse effects. Availability and implementation: drugMR: https://github.com/guillermocomesanacimadevila/drugMR; documentation: https://guillermocomesanacimadevila.github.io/drugMR/. Demo data: https://doi.org/10.5281/zenodo.22917384.
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