Year: 2025
Type: article
Abstract: Background Graphs or networks are ubiquitous data structures across scientific disciplines, from ecological and molecular to social networks. Visualisation is an important step to gain insight into network data, however most network analysis software packages, such as igraph and NetworkX , focus on statistical tools and offer limited visualisation options. Other packages offer powerful graphical user interfaces but rely on custom formats and implementations, which restricts interoperability with other scientific software. Methods iplotx is a Python software package designed to act as a universal visualiser for any network analysis package. A simple yet rich declarative style grammar enables customisation of any visual element including edge geometry, marker size and shape, labels, and groupings. Rendering relies on custom Matplotlib artists, which enables broad interoperability with other data visualisation libraries. Results iplotx supports eight different network and tree analysis packages (NetworkX, igraph, graph tool, Biopython, ETE, cogent3, dendropy, and scikit-bio) and implements a plug-in mechanism for universal input compatibility. It supports a wide spectrum of outputs including raster and vector images, animations, and interactive plots. The package implements unique features such as three-dimensional network visualisations and is fully compatible with the Python scientific software stack including seaborn, scipy, pandas, and Cartopy. Areas of application for iplotx include biomolecular and gene regulatory networks, protein-protein interactions, biochemical pathways, ecological networks, phylogenetics, and extend beyond biomedicine into economics, social, and transportation sciences. Conclusions Compared to extant software, iplotx offers broader interoperability, richer styling, a large gallery of examples, and extensive code testing. This makes iplotx a robust choice for the visualisation of any networks and trees in biomedicine and beyond.
Source: F1000Research
Author: Fabio Zanini
Institution: UNSW Sydney
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $1,350
Funder: Università degli Studi di Trento
OpenAlex ID: W7127318835