EzMAP: Easy Microbiome Analysis Platform

Abstract 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 efficien...

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Main Authors: Gnanendra Shanmugam, Song Hee Lee, Junhyun Jeon
Format: Article
Language:English
Published: BMC 2021-04-01
Series:BMC Bioinformatics
Subjects:
Online Access:https://doi.org/10.1186/s12859-021-04106-7
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author Gnanendra Shanmugam
Song Hee Lee
Junhyun Jeon
author_facet Gnanendra Shanmugam
Song Hee Lee
Junhyun Jeon
author_sort Gnanendra Shanmugam
collection DOAJ
description Abstract 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.
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spelling doaj.art-12ed04ccb0ad463a8e0f231d922f69ba2022-12-21T18:35:16ZengBMCBMC Bioinformatics1471-21052021-04-0122111010.1186/s12859-021-04106-7EzMAP: Easy Microbiome Analysis PlatformGnanendra Shanmugam0Song Hee Lee1Junhyun Jeon2Department of Biotechnology, Yeungnam UniversityDepartment of Biotechnology, Yeungnam UniversityDepartment of Biotechnology, Yeungnam UniversityAbstract 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.https://doi.org/10.1186/s12859-021-04106-7Microbiome analysis platformMicrobiome data analysisQIIME2 analysisMicrobiome user-friendly toolMicrobiome data visualization
spellingShingle Gnanendra Shanmugam
Song Hee Lee
Junhyun Jeon
EzMAP: Easy Microbiome Analysis Platform
BMC Bioinformatics
Microbiome analysis platform
Microbiome data analysis
QIIME2 analysis
Microbiome user-friendly tool
Microbiome data visualization
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 Microbiome analysis platform
Microbiome data analysis
QIIME2 analysis
Microbiome user-friendly tool
Microbiome data visualization
url https://doi.org/10.1186/s12859-021-04106-7
work_keys_str_mv AT gnanendrashanmugam ezmapeasymicrobiomeanalysisplatform
AT songheelee ezmapeasymicrobiomeanalysisplatform
AT junhyunjeon ezmapeasymicrobiomeanalysisplatform