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Efficient Inference of Large Prokaryotic Pangenomes with PanTA

Overview
Journal Genome Biol
Specialties Biology
Genetics
Date 2024 Aug 6
PMID 39107817
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Abstract

Pangenome inference is an indispensable step in bacterial genomics, yet its scalability poses a challenge due to the rapid growth of genomic collections. This paper presents PanTA, a software package designed for constructing pangenomes of large bacterial datasets, showing unprecedented efficiency levels multiple times higher than existing tools. PanTA introduces a novel mechanism to construct the pangenome progressively without rebuilding the accumulated collection from scratch. The progressive mode is shown to consume orders of magnitude less computational resources than existing solutions in managing growing datasets. The software is open source and is publicly available at https://github.com/amromics/panta and at 10.6084/m9.figshare.23724705 .

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References
1.
Li W, Godzik A . Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences. Bioinformatics. 2006; 22(13):1658-9. DOI: 10.1093/bioinformatics/btl158. View

2.
Zhao Y, Wu J, Yang J, Sun S, Xiao J, Yu J . PGAP: pan-genomes analysis pipeline. Bioinformatics. 2011; 28(3):416-8. PMC: 3268234. DOI: 10.1093/bioinformatics/btr655. View

3.
Nakamura T, Yamada K, Tomii K, Katoh K . Parallelization of MAFFT for large-scale multiple sequence alignments. Bioinformatics. 2018; 34(14):2490-2492. PMC: 6041967. DOI: 10.1093/bioinformatics/bty121. View

4.
Kim Y, Gu C, Kim H, Lee S . Current status of pan-genome analysis for pathogenic bacteria. Curr Opin Biotechnol. 2020; 63:54-62. DOI: 10.1016/j.copbio.2019.12.001. View

5.
Zeng L, Wang D, Hu N, Zhu Q, Chen K, Dong K . A Novel Pan-Genome Reverse Vaccinology Approach Employing a Negative-Selection Strategy for Screening Surface-Exposed Antigens against . Front Microbiol. 2017; 8:396. PMC: 5348505. DOI: 10.3389/fmicb.2017.00396. View