RecruitPlotEasy: An Advanced Read Recruitment Plot Tool for Assessing Metagenomic Population Abundance and Genetic Diversity

Kenji Gerhardt; Carlos A Ruiz-Perez; Luis M Rodriguez-R; Roth E Conrad; Konstantinos T Konstantinidis

doi:10.3389/fbinf.2021.826701

RecruitPlotEasy: An Advanced Read Recruitment Plot Tool for Assessing Metagenomic Population Abundance and Genetic Diversity

Front Bioinform. 2022 Jan 27:1:826701. doi: 10.3389/fbinf.2021.826701. eCollection 2021.

Authors

Kenji Gerhardt^{1

2}, Carlos A Ruiz-Perez^{1

2}, Luis M Rodriguez-R³, Roth E Conrad⁴, Konstantinos T Konstantinidis^{1

2

4

5}

Affiliations

¹ School of Biological Sciences, Atlanta, GA, United States.
² Center for Bioinformatics and Computational Genomics, Atlanta, GA, United States.
³ Department of Microbiology and Digital Science Center (DiSC), University of Innsbruck, Innsbruck, Austria.
⁴ Ocean Science & Engineering, Atlanta, GA, United States.
⁵ School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA, United States.

Abstract

Mapping of short metagenomic (or metatranscriptomic) read data to reference isolate or single-cell genomes or metagenome-assembled genomes (MAGs) to assess microbial population relative abundance and/or structure represents an essential task of many studies across environmental and clinical settings. The filtering for the quality of the read match and assessment of read mapping results are frequently performed without visual aids or with the assistance of visualizations produced through ad-hoc, in-house approaches. Here, we introduce RecruitPlotEasy, a fully automated, user-friendly pipeline for these purposes that integrates statistical approaches to quantify intra-population sequence and gene-content diversity and identify co-occurring relative populations in the sample. Hence, RecruitPlotEasy should also greatly facilitate population genetics studies. RecruitPlotEasy is implemented in Python and R languages and is freely available open source software under the Artistic License 2.0 from https://github.com/KGerhardt/RecruitPlotEasy.

Keywords: MAG; bioinformatics; metagenomics; population diversity; software.