evolSOM: an R Package for evolutionary conservation analysis with SOMs

• URL: http://arxiv.org/abs/2402.07948v1
• Date: Fri, 9 Feb 2024 20:33:48 GMT
• Title: evolSOM: an R Package for evolutionary conservation analysis with SOMs
• Authors: Santiago Prochetto, Renata Reinheimer, Georgina Stegmayer
• Abstract summary: We introduce evolSOM, a novel R package that utilizes Self-Organizing Maps (SOMs) to explore and visualize the conservation of biological variables. The package automatically calculates and graphically presents displacements, enabling efficient comparison and revealing conserved and displaced variables. Illustratively, we employed evolSOM to study the displacement of genes and phenotypic traits, successfully identifying potential drivers of phenotypic differentiation in grass leaves.
• Score: 0.4972323953932129
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Motivation: Unraveling the connection between genes and traits is crucial for solving many biological puzzles. Genes provide instructions for building cellular machinery, directing the processes that sustain life. RNA molecules and proteins, derived from these genetic instructions, play crucial roles in shaping cell structures, influencing reactions, and guiding behavior. This fundamental biological principle links genetic makeup to observable traits, but integrating and extracting meaningful relationships from this complex, multimodal data presents a significant challenge. Results: We introduce evolSOM, a novel R package that utilizes Self-Organizing Maps (SOMs) to explore and visualize the conservation of biological variables, easing the integration of phenotypic and genotypic attributes. By constructing species-specific or condition-specific SOMs that capture non-redundant patterns, evolSOM allows the analysis of displacement of biological variables between species or conditions. Variables displaced together suggest membership in the same regulatory network, and the nature of the displacement may hold biological significance. The package automatically calculates and graphically presents these displacements, enabling efficient comparison and revealing conserved and displaced variables. The package facilitates the integration of diverse phenotypic data types, enabling the exploration of potential gene drivers underlying observed phenotypic changes. Its user-friendly interface and visualization capabilities enhance the accessibility of complex network analyses. Illustratively, we employed evolSOM to study the displacement of genes and phenotypic traits, successfully identifying potential drivers of phenotypic differentiation in grass leaves. Availability: The package is open-source and is available at https://github.com/sanprochetto/evolSOM.

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