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TAMPA: interpretable analysis and visualization of metagenomics-based taxon abundance profiles

Varuni Sarwal, Jaqueline Brito, Serghei Mangul, View ORCID ProfileDavid Koslicki
doi: https://doi.org/10.1101/2022.04.28.489926
Varuni Sarwal
1Department of Computer Science, University of California Los Angeles, 580 Portola Plaza, Los Angeles, CA 90095, USA
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Jaqueline Brito
2Department of Clinical Pharmacy, University of Southern California, Los Angeles, California, 90089, United States
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Serghei Mangul
2Department of Clinical Pharmacy, University of Southern California, Los Angeles, California, 90089, United States
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David Koslicki
3Department of Computer Science and Engineering, The Pennsylvania State University, University Park, PA, USA
4Department of Biology, The Pennsylvania State University, University Park, PA, USA
5Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA, USA
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  • ORCID record for David Koslicki
  • For correspondence: dmk333@psu.edu
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Abstract

Metagenomic taxonomic profiling aims to predict the identity and relative abundance of taxa in a given whole genome sequencing metagenomic sample. A recent surge in computational methods that aim to accurately estimate taxonomic profiles, called taxonomic profilers, have motivated community driven efforts to create standardized benchmarking datasets and platforms, standardized taxonomic profile formats, as well as a benchmarking platform to assess tool performance. While this standardization is essential, there is currently a lack of tools to visualize the standardized output of the many existing taxonomic profilers, and benchmarking studies rely on a single value metrics to compare performance of tools and compare to benchmarking datasets. Here we report the development of TAMPA (Taxonomic metagenome profiling evaluation), a robust and easy-to-use method that allows scientists to easily interpret and interact with taxonomic profiles produced by the many different taxonomic profiler methods beyond the standard metrics used by the scientific community. We demonstrate the unique ability of TAMPA to provide important biological insights into the taxonomic differences between samples otherwise missed by commonly utilized metrics. Additionally, we show that TAMPA can help visualize the output of taxonomic profilers, enabling biologists to effectively choose the most appropriate profiling method to use on their metagenomics data. TAMPA is available on GitHub, Bioconda and Galaxy Toolshed at https://github.com/dkoslicki/TAMPA, and is released under the MIT license.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted April 29, 2022.
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TAMPA: interpretable analysis and visualization of metagenomics-based taxon abundance profiles
Varuni Sarwal, Jaqueline Brito, Serghei Mangul, David Koslicki
bioRxiv 2022.04.28.489926; doi: https://doi.org/10.1101/2022.04.28.489926
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TAMPA: interpretable analysis and visualization of metagenomics-based taxon abundance profiles
Varuni Sarwal, Jaqueline Brito, Serghei Mangul, David Koslicki
bioRxiv 2022.04.28.489926; doi: https://doi.org/10.1101/2022.04.28.489926

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