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An Overview of Bioinformatics Tools for DNA Meta-Barcoding Analysis of Microbial Communities of Bioaerosols: Digest for Microbiologists
High-throughput DNA sequencing (HTS) has changed our understanding of the microbial composition present in a wide range of environments. Applying HTS methods to air samples from different environments allows the identification and quantification (relative abundance) of the microorganisms present and...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7555798/ https://www.ncbi.nlm.nih.gov/pubmed/32911871 http://dx.doi.org/10.3390/life10090185 |
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author | Mbareche, Hamza Dumont-Leblond, Nathan Bilodeau, Guillaume J. Duchaine, Caroline |
author_facet | Mbareche, Hamza Dumont-Leblond, Nathan Bilodeau, Guillaume J. Duchaine, Caroline |
author_sort | Mbareche, Hamza |
collection | PubMed |
description | High-throughput DNA sequencing (HTS) has changed our understanding of the microbial composition present in a wide range of environments. Applying HTS methods to air samples from different environments allows the identification and quantification (relative abundance) of the microorganisms present and gives a better understanding of human exposure to indoor and outdoor bioaerosols. To make full use of the avalanche of information made available by these sequences, repeated measurements must be taken, community composition described, error estimates made, correlations of microbiota with covariates (variables) must be examined, and increasingly sophisticated statistical tests must be conducted, all by using bioinformatics tools. Knowing which analysis to conduct and which tools to apply remains confusing for bioaerosol scientists, as a litany of tools and data resources are now available for characterizing microbial communities. The goal of this review paper is to offer a guided tour through the bioinformatics tools that are useful in studying the microbial ecology of bioaerosols. This work explains microbial ecology features like alpha and beta diversity, multivariate analyses, differential abundances, taxonomic analyses, visualization tools and statistical tests using bioinformatics tools for bioaerosol scientists new to the field. It illustrates and promotes the use of selected bioinformatic tools in the study of bioaerosols and serves as a good source for learning the “dos and don’ts” involved in conducting a precise microbial ecology study. |
format | Online Article Text |
id | pubmed-7555798 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-75557982020-10-19 An Overview of Bioinformatics Tools for DNA Meta-Barcoding Analysis of Microbial Communities of Bioaerosols: Digest for Microbiologists Mbareche, Hamza Dumont-Leblond, Nathan Bilodeau, Guillaume J. Duchaine, Caroline Life (Basel) Review High-throughput DNA sequencing (HTS) has changed our understanding of the microbial composition present in a wide range of environments. Applying HTS methods to air samples from different environments allows the identification and quantification (relative abundance) of the microorganisms present and gives a better understanding of human exposure to indoor and outdoor bioaerosols. To make full use of the avalanche of information made available by these sequences, repeated measurements must be taken, community composition described, error estimates made, correlations of microbiota with covariates (variables) must be examined, and increasingly sophisticated statistical tests must be conducted, all by using bioinformatics tools. Knowing which analysis to conduct and which tools to apply remains confusing for bioaerosol scientists, as a litany of tools and data resources are now available for characterizing microbial communities. The goal of this review paper is to offer a guided tour through the bioinformatics tools that are useful in studying the microbial ecology of bioaerosols. This work explains microbial ecology features like alpha and beta diversity, multivariate analyses, differential abundances, taxonomic analyses, visualization tools and statistical tests using bioinformatics tools for bioaerosol scientists new to the field. It illustrates and promotes the use of selected bioinformatic tools in the study of bioaerosols and serves as a good source for learning the “dos and don’ts” involved in conducting a precise microbial ecology study. MDPI 2020-09-08 /pmc/articles/PMC7555798/ /pubmed/32911871 http://dx.doi.org/10.3390/life10090185 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Mbareche, Hamza Dumont-Leblond, Nathan Bilodeau, Guillaume J. Duchaine, Caroline An Overview of Bioinformatics Tools for DNA Meta-Barcoding Analysis of Microbial Communities of Bioaerosols: Digest for Microbiologists |
title | An Overview of Bioinformatics Tools for DNA Meta-Barcoding Analysis of Microbial Communities of Bioaerosols: Digest for Microbiologists |
title_full | An Overview of Bioinformatics Tools for DNA Meta-Barcoding Analysis of Microbial Communities of Bioaerosols: Digest for Microbiologists |
title_fullStr | An Overview of Bioinformatics Tools for DNA Meta-Barcoding Analysis of Microbial Communities of Bioaerosols: Digest for Microbiologists |
title_full_unstemmed | An Overview of Bioinformatics Tools for DNA Meta-Barcoding Analysis of Microbial Communities of Bioaerosols: Digest for Microbiologists |
title_short | An Overview of Bioinformatics Tools for DNA Meta-Barcoding Analysis of Microbial Communities of Bioaerosols: Digest for Microbiologists |
title_sort | overview of bioinformatics tools for dna meta-barcoding analysis of microbial communities of bioaerosols: digest for microbiologists |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7555798/ https://www.ncbi.nlm.nih.gov/pubmed/32911871 http://dx.doi.org/10.3390/life10090185 |
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