drugMR: A multi-omics pipeline for genetically anchored drug-target discovery
- 1Cardiff University
Abstract
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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BibTeX
@misc{cimadevila2026drugmr,
title = {{drugMR: A multi-omics pipeline for genetically anchored drug-target discovery}},
author = {G. Comesana Cimadevila and M.-J. Dib and M. Bracher-Smith and F. Ducotterd and D. A. Salih and N. J. Bray and E. Simmonds and V. Escott-Price},
howpublished = {bioRxiv},
year = {2026},
month = oct,
doi = {10.64898/2026.10.01.756031},
url = {https://www.biorxiv.org/content/10.64898/2026.10.01.756031v1},
note = {CC BY},
}
RIS
TY - UNPB
TI - drugMR: A multi-omics pipeline for genetically anchored drug-target discovery
AU - G. Comesana Cimadevila
AU - M.-J. Dib
AU - M. Bracher-Smith
AU - F. Ducotterd
AU - D. A. Salih
AU - N. J. Bray
AU - E. Simmonds
AU - V. Escott-Price
PY - 2026
DA - 2026/10/01
PB - bioRxiv
DO - 10.64898/2026.10.01.756031
UR - https://www.biorxiv.org/content/10.64898/2026.10.01.756031v1
AB - 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.
ER -