Computational protocol to identify shared transcriptional risks and mutually beneficial compounds between diseases.
STAR Protoc
; 5(1): 102883, 2024 Mar 15.
Article
en En
| MEDLINE
| ID: mdl-38354084
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.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Contexto en salud:
1_ASSA2030
Problema de salud:
1_sistemas_informacao_saude
Asunto principal:
Flujo de Trabajo
Tipo de estudio:
Etiology_studies
/
Guideline
/
Risk_factors_studies
Idioma:
En
Revista:
STAR Protoc
Año:
2024
Tipo del documento:
Article