Gao, Hua and Zhang, Mao and Baylis, Richard A. and Wang, Fudi and Björkegren, Johan L.M. and Kovacic, Jason J. and Ruusalepp, Arno and Leeper, Nicholas J. (2024) Computational protocol to identify shared transcriptional risks and mutually beneficial compounds between diseases. STAR Protocols, 5 (1). p. 102883. ISSN 26661667
Full text not available from this repository.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).
| Item Type: | Article |
|---|---|
| Subjects: | R Medicine > R Medicine (General) |
| Depositing User: | Repository Administrator |
| Date Deposited: | 15 Dec 2024 04:10 |
| Last Modified: | 15 Dec 2024 04:10 |
| URI: | https://eprints.victorchang.edu.au/id/eprint/1527 |
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