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Computational protocol to identify shared transcriptional risks and mutually beneficial compounds between diseases. STAR protocols Gao, H., Zhang, M., Baylis, R. A., Wang, F., Björkegren, J. L., Kovacic, J. J., Ruusalepp, A., Leeper, N. J. 2024; 5 (1): 102883

Abstract

The accumulation of omics and biobank resources allows for a genome-wide understanding of the shared pathologic mechanisms between diseases and for strategies to identify drugs that could be repurposed as novel treatments. Here, we present a computational protocol, implemented as a Snakemake workflow, to identify shared transcriptional processes and screen compounds that could result in mutual benefit. This protocol also includes a description of a pharmacovigilance study designed to validate the effect of compounds using electronic health records. For complete details on the use and execution of this protocol, please refer to Gao et al.1 and Baylis et al.2.

View details for DOI 10.1016/j.xpro.2024.102883

View details for PubMedID 38354084