Matreex: compact and interactive visualisation for scalable studies of large gene families

Abstract

Studying gene family evolution strongly benefits from insightful visualisations. However, the ever-growing number of sequenced genomes is leading to increasingly larger gene families, which challenges existing gene tree visualisations. Indeed, most of them present users with a dilemma: display complete but intractable gene trees, or collapse subtrees, thereby hiding their children information. Here, we introduce Matreex, a new dynamic tool to scale-up the visualisation of gene families. Matreex key idea is to use "phylogenetic" profiles, which are dense representations of gene repertoires, to minimise the information loss when collapsing subtrees. We illustrate Matreex usefulness with three biological applications. First, using the textbook example of visual opsins, we show Matreex potential to create easily interpretable figures for teaching and outreach. Secondly, by displaying 22 intraflagellar transport gene families across 622 species cumulating 5500 representatives, we show how Matreex can be used to automate large-scale analyses of gene presence-absence. Notably, we report for the first time the complete loss of intraflagellar transport in the myxozoan Thelohanellus kitauei. Finally, we demonstrate on the MutS family the power of combining gene trees and phylogenetic profiles to delve into precise evolutionary analyses of large multi-copy gene families. Matreex is available from the Python Package Index (pip install matreex) with the source code and documentation available at https://github.com/DessimozLab/matreex.

TreeProfiler: A command-line tool for computing and visualizing phylogenetic profiles against large trees

“…There are available bioinformatic tools for this purpose (Huerta-Cepas et al, 2016; Revell, 2012; Stamatakis, 2014; Suchard et al, 2018; Sukumaran & Holder, 2010), but they all demand programming skills and ad hoc implementations. Other tools have been developed that provide more straightforward and user-friendly interfaces, but they are usually restricted to specific scenarios such as profiling orthologous groups (e.g., eggNOG (Hernández-Plaza et al, 2022), Matreex (Rossier et al, 2023), PhyloProfile (Tran et al, 2018)), domain architectures (e.g., PhyloPro2.0 (Cromar et al, 2016)) or metagenomics profiling (e.g., Graphlan (Asnicar et al, 2015), TAMPA (Sarwal et al, 2023)).…”