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EzMAP: Easy Microbiome Analysis Platform
BACKGROUND: The rapid advances in next-generation sequencing technologies have revolutionized the microbiome research by greatly increasing our ability to understand diversity of microbes in a given sample. Over the past decade, several computational pipelines have been developed to efficiently proc...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8028061/ https://www.ncbi.nlm.nih.gov/pubmed/33827413 http://dx.doi.org/10.1186/s12859-021-04106-7 |
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author | Shanmugam, Gnanendra Lee, Song Hee Jeon, Junhyun |
author_facet | Shanmugam, Gnanendra Lee, Song Hee Jeon, Junhyun |
author_sort | Shanmugam, Gnanendra |
collection | PubMed |
description | BACKGROUND: The rapid advances in next-generation sequencing technologies have revolutionized the microbiome research by greatly increasing our ability to understand diversity of microbes in a given sample. Over the past decade, several computational pipelines have been developed to efficiently process and annotate these microbiome data. However, most of these pipelines require an implementation of additional tools for downstream analyses as well as advanced programming skills. RESULTS: Here we introduce a user-friendly microbiome analysis platform, EzMAP (Easy Microbiome Analysis Platform), which was developed using Java Swings, Java Script and R programming language. EzMAP is a standalone package providing graphical user interface, enabling easy access to all the functionalities of QIIME2 (Quantitative Insights Into Microbial Ecology) as well as streamlined downstream analyses using QIIME2 output as input. This platform is designed to give users the detailed reports and the intermediate output files that are generated progressively. The users are allowed to download the features/OTU table (.biom;.tsv;.xls), representative sequences (.fasta) and phylogenetic tree (.nwk), taxonomy assignment file (optional). For downstream analyses, users are allowed to perform relative abundances (at all taxonomical levels), community comparison (alpha and beta diversity, core microbiome), differential abundances (DESeq2 and linear discriminant analysis) and functional prediction (PICRust, Tax4Fun and FunGuilds). Our case study using a published rice microbiome dataset demonstrates intuitive user interface and great accessibility of the EzMAP. CONCLUSIONS: This EzMAP allows users to consolidate the microbiome analysis processes from raw sequence processing to downstream analyses specific for individual projects. We believe that this will be an invaluable tool for the beginners in their microbiome data analysis. This platform is freely available at https://github.com/gnanibioinfo/EzMAP and will be continually updated for adoption of changes in methods and approaches. |
format | Online Article Text |
id | pubmed-8028061 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-80280612021-04-08 EzMAP: Easy Microbiome Analysis Platform Shanmugam, Gnanendra Lee, Song Hee Jeon, Junhyun BMC Bioinformatics Software BACKGROUND: The rapid advances in next-generation sequencing technologies have revolutionized the microbiome research by greatly increasing our ability to understand diversity of microbes in a given sample. Over the past decade, several computational pipelines have been developed to efficiently process and annotate these microbiome data. However, most of these pipelines require an implementation of additional tools for downstream analyses as well as advanced programming skills. RESULTS: Here we introduce a user-friendly microbiome analysis platform, EzMAP (Easy Microbiome Analysis Platform), which was developed using Java Swings, Java Script and R programming language. EzMAP is a standalone package providing graphical user interface, enabling easy access to all the functionalities of QIIME2 (Quantitative Insights Into Microbial Ecology) as well as streamlined downstream analyses using QIIME2 output as input. This platform is designed to give users the detailed reports and the intermediate output files that are generated progressively. The users are allowed to download the features/OTU table (.biom;.tsv;.xls), representative sequences (.fasta) and phylogenetic tree (.nwk), taxonomy assignment file (optional). For downstream analyses, users are allowed to perform relative abundances (at all taxonomical levels), community comparison (alpha and beta diversity, core microbiome), differential abundances (DESeq2 and linear discriminant analysis) and functional prediction (PICRust, Tax4Fun and FunGuilds). Our case study using a published rice microbiome dataset demonstrates intuitive user interface and great accessibility of the EzMAP. CONCLUSIONS: This EzMAP allows users to consolidate the microbiome analysis processes from raw sequence processing to downstream analyses specific for individual projects. We believe that this will be an invaluable tool for the beginners in their microbiome data analysis. This platform is freely available at https://github.com/gnanibioinfo/EzMAP and will be continually updated for adoption of changes in methods and approaches. BioMed Central 2021-04-07 /pmc/articles/PMC8028061/ /pubmed/33827413 http://dx.doi.org/10.1186/s12859-021-04106-7 Text en © The Author(s) 2021 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/. The Creative Commons Public Domain Dedication waiver (http://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 Shanmugam, Gnanendra Lee, Song Hee Jeon, Junhyun EzMAP: Easy Microbiome Analysis Platform |
title | EzMAP: Easy Microbiome Analysis Platform |
title_full | EzMAP: Easy Microbiome Analysis Platform |
title_fullStr | EzMAP: Easy Microbiome Analysis Platform |
title_full_unstemmed | EzMAP: Easy Microbiome Analysis Platform |
title_short | EzMAP: Easy Microbiome Analysis Platform |
title_sort | ezmap: easy microbiome analysis platform |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8028061/ https://www.ncbi.nlm.nih.gov/pubmed/33827413 http://dx.doi.org/10.1186/s12859-021-04106-7 |
work_keys_str_mv | AT shanmugamgnanendra ezmapeasymicrobiomeanalysisplatform AT leesonghee ezmapeasymicrobiomeanalysisplatform AT jeonjunhyun ezmapeasymicrobiomeanalysisplatform |