bioRxivEvolutionary Biology
Matreex: compact and interactive visualisation for scalable studies of large gene families
V. Rossier, C. Train, Y. Nevers, M. Robinson-Rechavi, C. Dessimoz
Abstract
Studying gene family evolution strongly benefits from insightful visualisations. However, the evergrowing 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 childrens information. Here, we introduce Matreex, a new dynamic tool to scale-up the visualisation of gene families. Matreexs 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, 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. 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, using the textbook example of visual opsins, we show Matreexs potential to create easily interpretable figures for teaching and outreach. Matreex is available from the Python Package Index (pip install matreex) with the source code and documentation available at https://github.com/DessimozLab/matreex.
- organism: human
- organism: mouse
- organism: zebrafish
- assay: proteomics
- assay: metagenomics
- research focus: clustering
- research focus: gene regulatory network inference
- research focus: cell type annotation
- research focus: benchmarking
- approach: deep learning
- approach: statistical model
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