Genopyc: a python library for investigating the functional effects of genomic variants associated to complex diseases.


Journal

Bioinformatics (Oxford, England)
ISSN: 1367-4811
Titre abrégé: Bioinformatics
Pays: England
ID NLM: 9808944

Informations de publication

Date de publication:
18 Jun 2024
Historique:
received: 29 11 2023
revised: 21 05 2024
accepted: 14 06 2024
medline: 18 6 2024
pubmed: 18 6 2024
entrez: 18 6 2024
Statut: aheadofprint

Résumé

Understanding the genetic basis of complex diseases is one of the main challenges in modern genomics. However, current tools often lack the versatility to efficiently analyze the intricate relationships between genetic variations and disease outcomes. To address this, we introduce Genopyc, a novel Python library designed for comprehensive investigation of how the variants associated to complex diseases affects downstream pathways. Genopyc offers an extensive suite of functions for heterogeneous data mining and visualization, enabling researchers to delve into and integrate biological information from large-scale genomic datasets. In this work, we present the Genopyc library through application to real-world genome wide association studies variants. Using Genopyc to investigate the functional consequences of variants associated to intervertebral disc degeneration (IDD) enabled a deeper understanding of the potential dysregulated pathways involved in the disease, which can be explored and visualized by exploiting the functionalities featured in the package. Genopyc emerges as a powerful asset for researchers, facilitating the investigation of complex diseases paving the way for more targeted therapeutic interventions. Genopyc is available on pip https://pypi.org/project/genopyc/.The source code of Genopyc is available at https://github.com/freh-g/genopyc. A tutorial notebook is available at https://github.com/freh-g/genopyc/blob/main/tutorials/Genopyc_tutorial_notebook.ipynbFinally, a detailed documentation is available at: https://genopyc.readthedocs.io/en/latest/.

Identifiants

pubmed: 38889282
pii: 7695869
doi: 10.1093/bioinformatics/btae379
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© The Author(s) 2024. Published by Oxford University Press.

Auteurs

Francesco Gualdi (F)

Integrative biomedical informatics, Research program on Biomedical informatics (IBI-GRIB), Hospital del mar medical research institute IMIM Department of experimental and health sciences, Barcelona, E-08003, Spain.
Structural bioinformatics lab, Research program on Biomedical informatics (SBI-GRIB), Hospital del mar medical research institute IMIM Department of Experimental and health sciences, Barcelona, E-08003, Spain.

Baldomero Oliva (B)

Structural bioinformatics lab, Research program on Biomedical informatics (SBI-GRIB), Hospital del mar medical research institute IMIM Department of Experimental and health sciences, Barcelona, E-08003, Spain.

Janet Piñero (J)

Integrative biomedical informatics, Research program on Biomedical informatics (IBI-GRIB), Hospital del mar medical research institute IMIM Department of experimental and health sciences, Barcelona, E-08003, Spain.
Medbioinformatics Solutions SL, Barcelona, Spain.

Classifications MeSH