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SHAMAN: a user-friendly website for metataxonomic analysis from raw reads to statistical analysis.


ABSTRACT: BACKGROUND:Comparing the composition of microbial communities among groups of interest (e.g., patients vs healthy individuals) is a central aspect in microbiome research. It typically involves sequencing, data processing, statistical analysis and graphical display. Such an analysis is normally obtained by using a set of different applications that require specific expertise for installation, data processing and in some cases, programming skills. RESULTS:Here, we present SHAMAN, an interactive web application we developed in order to facilitate the use of (i) a bioinformatic workflow for metataxonomic analysis, (ii) a reliable statistical modelling and (iii) to provide the largest panel of interactive visualizations among the applications that are currently available. SHAMAN is specifically designed for non-expert users. A strong benefit is to use an integrated version of the different analytic steps underlying a proper metagenomic analysis. The application is freely accessible at http://shaman.pasteur.fr/ , and may also work as a standalone application with a Docker container (aghozlane/shaman), conda and R. The source code is written in R and is available at https://github.com/aghozlane/shaman . Using two different datasets (a mock community sequencing and a published 16S rRNA metagenomic data), we illustrate the strengths of SHAMAN in quickly performing a complete metataxonomic analysis. CONCLUSIONS:With SHAMAN, we aim at providing the scientific community with a platform that simplifies reproducible quantitative analysis of metagenomic data.

SUBMITTER: Volant S 

PROVIDER: S-EPMC7430814 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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SHAMAN: a user-friendly website for metataxonomic analysis from raw reads to statistical analysis.

Volant Stevenn S   Lechat Pierre P   Woringer Perrine P   Motreff Laurence L   Campagne Pascal P   Malabat Christophe C   Kennedy Sean S   Ghozlane Amine A  

BMC bioinformatics 20200810 1


<h4>Background</h4>Comparing the composition of microbial communities among groups of interest (e.g., patients vs healthy individuals) is a central aspect in microbiome research. It typically involves sequencing, data processing, statistical analysis and graphical display. Such an analysis is normally obtained by using a set of different applications that require specific expertise for installation, data processing and in some cases, programming skills.<h4>Results</h4>Here, we present SHAMAN, an  ...[more]

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