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iMAP: an integrated bioinformatics and visualization pipeline for microbiome data analysis

BACKGROUND: One of the major challenges facing investigators in the microbiome field is turning large numbers of reads generated by next-generation sequencing (NGS) platforms into biological knowledge. Effective analytical workflows that guarantee reproducibility, repeatability, and result provenanc...

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Autores principales: Buza, Teresia M., Tonui, Triza, Stomeo, Francesca, Tiambo, Christian, Katani, Robab, Schilling, Megan, Lyimo, Beatus, Gwakisa, Paul, Cattadori, Isabella M., Buza, Joram, Kapur, Vivek
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6610863/
https://www.ncbi.nlm.nih.gov/pubmed/31269897
http://dx.doi.org/10.1186/s12859-019-2965-4
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author Buza, Teresia M.
Tonui, Triza
Stomeo, Francesca
Tiambo, Christian
Katani, Robab
Schilling, Megan
Lyimo, Beatus
Gwakisa, Paul
Cattadori, Isabella M.
Buza, Joram
Kapur, Vivek
author_facet Buza, Teresia M.
Tonui, Triza
Stomeo, Francesca
Tiambo, Christian
Katani, Robab
Schilling, Megan
Lyimo, Beatus
Gwakisa, Paul
Cattadori, Isabella M.
Buza, Joram
Kapur, Vivek
author_sort Buza, Teresia M.
collection PubMed
description BACKGROUND: One of the major challenges facing investigators in the microbiome field is turning large numbers of reads generated by next-generation sequencing (NGS) platforms into biological knowledge. Effective analytical workflows that guarantee reproducibility, repeatability, and result provenance are essential requirements of modern microbiome research. For nearly a decade, several state-of-the-art bioinformatics tools have been developed for understanding microbial communities living in a given sample. However, most of these tools are built with many functions that require an in-depth understanding of their implementation and the choice of additional tools for visualizing the final output. Furthermore, microbiome analysis can be time-consuming and may even require more advanced programming skills which some investigators may be lacking. RESULTS: We have developed a wrapper named iMAP (Integrated Microbiome Analysis Pipeline) to provide the microbiome research community with a user-friendly and portable tool that integrates bioinformatics analysis and data visualization. The iMAP tool wraps functionalities for metadata profiling, quality control of reads, sequence processing and classification, and diversity analysis of operational taxonomic units. This pipeline is also capable of generating web-based progress reports for enhancing an approach referred to as review-as-you-go (RAYG). For the most part, the profiling of microbial community is done using functionalities implemented in Mothur or QIIME2 platform. Also, it uses different R packages for graphics and R-markdown for generating progress reports. We have used a case study to demonstrate the application of the iMAP pipeline. CONCLUSIONS: The iMAP pipeline integrates several functionalities for better identification of microbial communities present in a given sample. The pipeline performs in-depth quality control that guarantees high-quality results and accurate conclusions. The vibrant visuals produced by the pipeline facilitate a better understanding of the complex and multidimensional microbiome data. The integrated RAYG approach enables the generation of web-based reports, which provides the investigators with the intermediate output that can be reviewed progressively. The intensively analyzed case study set a model for microbiome data analysis. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-019-2965-4) contains supplementary material, which is available to authorized users.
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spelling pubmed-66108632019-07-16 iMAP: an integrated bioinformatics and visualization pipeline for microbiome data analysis Buza, Teresia M. Tonui, Triza Stomeo, Francesca Tiambo, Christian Katani, Robab Schilling, Megan Lyimo, Beatus Gwakisa, Paul Cattadori, Isabella M. Buza, Joram Kapur, Vivek BMC Bioinformatics Software BACKGROUND: One of the major challenges facing investigators in the microbiome field is turning large numbers of reads generated by next-generation sequencing (NGS) platforms into biological knowledge. Effective analytical workflows that guarantee reproducibility, repeatability, and result provenance are essential requirements of modern microbiome research. For nearly a decade, several state-of-the-art bioinformatics tools have been developed for understanding microbial communities living in a given sample. However, most of these tools are built with many functions that require an in-depth understanding of their implementation and the choice of additional tools for visualizing the final output. Furthermore, microbiome analysis can be time-consuming and may even require more advanced programming skills which some investigators may be lacking. RESULTS: We have developed a wrapper named iMAP (Integrated Microbiome Analysis Pipeline) to provide the microbiome research community with a user-friendly and portable tool that integrates bioinformatics analysis and data visualization. The iMAP tool wraps functionalities for metadata profiling, quality control of reads, sequence processing and classification, and diversity analysis of operational taxonomic units. This pipeline is also capable of generating web-based progress reports for enhancing an approach referred to as review-as-you-go (RAYG). For the most part, the profiling of microbial community is done using functionalities implemented in Mothur or QIIME2 platform. Also, it uses different R packages for graphics and R-markdown for generating progress reports. We have used a case study to demonstrate the application of the iMAP pipeline. CONCLUSIONS: The iMAP pipeline integrates several functionalities for better identification of microbial communities present in a given sample. The pipeline performs in-depth quality control that guarantees high-quality results and accurate conclusions. The vibrant visuals produced by the pipeline facilitate a better understanding of the complex and multidimensional microbiome data. The integrated RAYG approach enables the generation of web-based reports, which provides the investigators with the intermediate output that can be reviewed progressively. The intensively analyzed case study set a model for microbiome data analysis. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-019-2965-4) contains supplementary material, which is available to authorized users. BioMed Central 2019-07-03 /pmc/articles/PMC6610863/ /pubmed/31269897 http://dx.doi.org/10.1186/s12859-019-2965-4 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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.
spellingShingle Software
Buza, Teresia M.
Tonui, Triza
Stomeo, Francesca
Tiambo, Christian
Katani, Robab
Schilling, Megan
Lyimo, Beatus
Gwakisa, Paul
Cattadori, Isabella M.
Buza, Joram
Kapur, Vivek
iMAP: an integrated bioinformatics and visualization pipeline for microbiome data analysis
title iMAP: an integrated bioinformatics and visualization pipeline for microbiome data analysis
title_full iMAP: an integrated bioinformatics and visualization pipeline for microbiome data analysis
title_fullStr iMAP: an integrated bioinformatics and visualization pipeline for microbiome data analysis
title_full_unstemmed iMAP: an integrated bioinformatics and visualization pipeline for microbiome data analysis
title_short iMAP: an integrated bioinformatics and visualization pipeline for microbiome data analysis
title_sort imap: an integrated bioinformatics and visualization pipeline for microbiome data analysis
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6610863/
https://www.ncbi.nlm.nih.gov/pubmed/31269897
http://dx.doi.org/10.1186/s12859-019-2965-4
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