Abstract
Motivation Understanding the genetic basis of complex diseases is a paramount challenge in modern genomics. However, current tools often lack the versatility to efficiently analyze the intricate relation-ships between genetic variations and disease outcomes. To address this, we introduce Genopyc, a novel Python library designed for comprehensive investigation of the genetics underlying complex dis-eases. 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 da-tasets with ease.
Results In this study, we present the Genopyc library through application to real-world genome wide association studies variants. Using Genopyc to investigate 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, fostering advancements in the un-derstanding of complex diseases and thus paving the way for more targeted therapeutic interventions. Availability: Genopyc is available at pip (https://pypi.org/project/genopyc/) and the source code of Genopyc is available at https://github.com/freh-g/genopyc
Contact francesco.gualdi01{at}estudiant.upf.edu
Supplementary information supplementary data are available at Bioinformatics online.
Competing Interest Statement
The authors have declared no competing interest.
