Impact of DNA amount and number of PCR cycle on a MOCK sequencing. SHAMAN MOCK

Profiling differences in microbiome composition regarding a healthy or a disease phenotype is central in microbiome research. It typically involves the sequencing, the data processing, the statistical analysis and the graphical representation of the detected signatures. This process is currently addressed through several separated applications that requires expertise for installation, data processing and in some case, programming skills. We present SHAMAN, which is an interactive web application that facilitates the use of a bioinformatic workflow for metataxonomic analysis, a robust statistical modelling and provides the largest panel of interactive visualizations among current solutions. SHAMAN is specifically designed for biologist for which a unified experience of the different step of the metagenomic analysis could make a difference in term of productivity. It is freely accessible at http://shaman.pasteur.fr/, but also work as a standalone application with docker (aghozlane/shaman), conda and R. The source code is written in R and is available at https://github.com/aghozlane/shaman. Using a mock community sequencing and a published 16S metagenomic dataset, we show here that SHAMAN allows to perform a complete metataxonomic analysis.

针对健康或疾病表型（phenotype）的微生物组（microbiome）组成差异分析，是微生物组研究的核心内容。该流程通常涵盖测序、数据处理、统计分析以及检测到的特征的可视化呈现。当前该流程需通过多个独立应用程序完成，且这些程序的安装、数据处理环节往往需要专业知识，部分场景下还需具备编程技能。我们推出的SHAMAN是一款交互式网页应用，可简化宏分类组学分析（metataxonomic analysis）的生物信息学流程、支持稳健的统计建模，且拥有当前同类方案中最丰富的交互式可视化面板集合。SHAMAN专为生物学家打造，其统一的宏基因组分析（metagenomic analysis）全流程操作体验可显著提升研究效率。该工具可通过http://shaman.pasteur.fr/免费访问，同时也可作为独立应用程序，通过Docker（镜像名aghozlane/shaman）、Conda及R环境部署。其源代码采用R语言编写，托管于https://github.com/aghozlane/shaman。本研究借助模拟群落（mock community）测序数据与已发表的16S宏基因组数据集，验证了SHAMAN可完整完成宏分类组学分析流程。