Cargando…

POSMM: an efficient alignment-free metagenomic profiler that complements alignment-based profiling

We present here POSMM (pronounced ‘Possum’), Python-Optimized Standard Markov Model classifier, which is a new incarnation of the Markov model approach to metagenomic sequence analysis. Built on the top of a rapid Markov model based classification algorithm SMM, POSMM reintroduces high sensitivity a...

Descripción completa

Detalles Bibliográficos
Autores principales: Burks, David J., Pusadkar, Vaidehi, Azad, Rajeev K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9993663/
https://www.ncbi.nlm.nih.gov/pubmed/36890583
http://dx.doi.org/10.1186/s40793-023-00476-y
_version_ 1784902560037994496
author Burks, David J.
Pusadkar, Vaidehi
Azad, Rajeev K.
author_facet Burks, David J.
Pusadkar, Vaidehi
Azad, Rajeev K.
author_sort Burks, David J.
collection PubMed
description We present here POSMM (pronounced ‘Possum’), Python-Optimized Standard Markov Model classifier, which is a new incarnation of the Markov model approach to metagenomic sequence analysis. Built on the top of a rapid Markov model based classification algorithm SMM, POSMM reintroduces high sensitivity associated with alignment-free taxonomic classifiers to probe whole genome or metagenome datasets of increasingly prohibitive sizes. Logistic regression models generated and optimized using the Python sklearn library, transform Markov model probabilities to scores suitable for thresholding. Featuring a dynamic database-free approach, models are generated directly from genome fasta files per run, making POSMM a valuable accompaniment to many other programs. By combining POSMM with ultrafast classifiers such as Kraken2, their complementary strengths can be leveraged to produce higher overall accuracy in metagenomic sequence classification than by either as a standalone classifier. POSMM is a user-friendly and highly adaptable tool designed for broad use by the metagenome scientific community. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40793-023-00476-y.
format Online
Article
Text
id pubmed-9993663
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-99936632023-03-09 POSMM: an efficient alignment-free metagenomic profiler that complements alignment-based profiling Burks, David J. Pusadkar, Vaidehi Azad, Rajeev K. Environ Microbiome Software We present here POSMM (pronounced ‘Possum’), Python-Optimized Standard Markov Model classifier, which is a new incarnation of the Markov model approach to metagenomic sequence analysis. Built on the top of a rapid Markov model based classification algorithm SMM, POSMM reintroduces high sensitivity associated with alignment-free taxonomic classifiers to probe whole genome or metagenome datasets of increasingly prohibitive sizes. Logistic regression models generated and optimized using the Python sklearn library, transform Markov model probabilities to scores suitable for thresholding. Featuring a dynamic database-free approach, models are generated directly from genome fasta files per run, making POSMM a valuable accompaniment to many other programs. By combining POSMM with ultrafast classifiers such as Kraken2, their complementary strengths can be leveraged to produce higher overall accuracy in metagenomic sequence classification than by either as a standalone classifier. POSMM is a user-friendly and highly adaptable tool designed for broad use by the metagenome scientific community. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40793-023-00476-y. BioMed Central 2023-03-08 /pmc/articles/PMC9993663/ /pubmed/36890583 http://dx.doi.org/10.1186/s40793-023-00476-y Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Software
Burks, David J.
Pusadkar, Vaidehi
Azad, Rajeev K.
POSMM: an efficient alignment-free metagenomic profiler that complements alignment-based profiling
title POSMM: an efficient alignment-free metagenomic profiler that complements alignment-based profiling
title_full POSMM: an efficient alignment-free metagenomic profiler that complements alignment-based profiling
title_fullStr POSMM: an efficient alignment-free metagenomic profiler that complements alignment-based profiling
title_full_unstemmed POSMM: an efficient alignment-free metagenomic profiler that complements alignment-based profiling
title_short POSMM: an efficient alignment-free metagenomic profiler that complements alignment-based profiling
title_sort posmm: an efficient alignment-free metagenomic profiler that complements alignment-based profiling
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9993663/
https://www.ncbi.nlm.nih.gov/pubmed/36890583
http://dx.doi.org/10.1186/s40793-023-00476-y
work_keys_str_mv AT burksdavidj posmmanefficientalignmentfreemetagenomicprofilerthatcomplementsalignmentbasedprofiling
AT pusadkarvaidehi posmmanefficientalignmentfreemetagenomicprofilerthatcomplementsalignmentbasedprofiling
AT azadrajeevk posmmanefficientalignmentfreemetagenomicprofilerthatcomplementsalignmentbasedprofiling