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

Gualdi, Francesco; Oliva Miguel, Baldomero; Piñero González, Janet, 1977-

doi:http://dx.doi.org/10.1093/bioinformatics/btae379

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

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Gualdi F, Oliva B, Piñero J. Genopyc: a Python library for investigating the functional effects of genomic variants associated to complex diseases. Bioinformatics. 2024 Jun 3;40(6):btae379. DOI: 10.1093/bioinformatics/btae379

Abstract

Motivation: Integrative Biomedicl Informatics, Research Program on Biomedical Informatics (IBI - GRIB), Hospital Del Mar Medical Research Institute (IMIM), Department of Experimental and Health Sciences, Universitat Pompeu Fabra (UPF) C/ del Dr. Aiguader 88 Barcelona 08003 Spain.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. Results: 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 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. Availability and implementation: 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.ipynb. Finally, a detailed documentation is available at: https://genopyc.readthedocs.io/en/latest/.