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Title: | Snowflake: visualizing microbiome abundance tables as multivariate bipartite graphs | Authors: | PEETERS, Jannes Bot, Daniel ROVELO RUIZ, Gustavo AERTS, Jan |
Issue Date: | 2024 | Publisher: | FRONTIERS MEDIA SA | Source: | Frontiers in bioinformatics, 4 (Art N° 1331043) | Abstract: | Current visualizations in microbiome research rely on aggregations in taxonomic classifications or do not show less abundant taxa. We introduce Snowflake: a new visualization method that creates a clear overview of the microbiome composition in collected samples without losing any information due to classification or neglecting less abundant reads. Snowflake displays every observed OTU/ASV in the microbiome abundance table and provides a solution to include the data's hierarchical structure and additional information obtained from downstream analysis (e.g., alpha- and beta-diversity) and metadata. Based on the value-driven ICE-T evaluation methodology, Snowflake was positively received. Experts in microbiome research found the visualizations to be user-friendly and detailed and liked the possibility of including and relating additional information to the microbiome's composition. Exploring the topological structure of the microbiome abundance table allows them to quickly identify which taxa are unique to specific samples and which are shared among multiple samples (i.e., separating sample-specific taxa from the core microbiome), and see the compositional differences between samples. An R package for constructing and visualizing Snowflake microbiome composition graphs is available at https://gitlab.com/vda-lab/snowflake. | Notes: | Aerts, J (corresponding author), Katholieke Univ Leuven, Dept Biosyst, Visual Data Anal Lab, Leuven, Belgium. jan.aerts@kuleuven.be |
Keywords: | microbiome composition;taxonomy;metagenomics;visualization method;visualization application | Document URI: | http://hdl.handle.net/1942/42531 | e-ISSN: | 2673-7647 | DOI: | 10.3389/fbinf.2024.1331043 | ISI #: | 001163858400001 | Rights: | 2024 Peeters, Bot, Rovelo Ruiz and Aerts. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. | Category: | A1 | Type: | Journal Contribution |
Appears in Collections: | Research publications |
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