一种基于Galaxy平台的微生物数据分析框架
创作:高春辉 审核:szx 2018年06月02日
  • ASaiM是一个模块化和用户友好的用于微生物数据分析的框架;
  • 基于开源Galaxy平台,集成了超过100种分析工具,内置若干参考分析流程,通过Docker方式快速部署;
  • 避免了Mothur、QIIME等命令行工具难学难用和MG-RAST、EBI等在线服务缺少透明性的缺点;
  • 可用于组装、提取、探索和可视化宏分类学、宏基因组和宏转录组序列中的微生物信息;
  • ASaiM可在PC机上运行,同时是开源软件(Apache 2协议),有丰富文档。
主编推荐语
szx
GigaScience上介绍的一种新的微生物数据分析框架——ASaiM,可用于微生物数据的组装、提取、可视化。
关键字
延伸阅读本研究的原文信息和链接出处,以及相关解读和评论文章。欢迎读者朋友们推荐!
图片
GigaScience [IF:5.993]

ASaiM: a Galaxy-based framework to analyze microbiota data

ASaiM:一个基于Galaxy的微生物数据分析框架

10.1093/gigascience/giy057

2018-05-22, Article

Abstract & Authors:展开

Abstract:收起
Background New generations of sequencing platforms coupled to numerous bioinformatics tools has led to rapid technological progress in metagenomics and metatranscriptomics to investigate complex microorganism communities. Nevertheless, a combination of different bioinformatic tools remains necessary to draw conclusions out of microbiota studies. Modular and user-friendly tools would greatly improve such studies. Findings We therefore developed ASaiM, an Open-Source Galaxy-based framework dedicated to microbiota data analyses. ASaiM provides an extensive collection of tools to assemble, extract, explore and visualize microbiota information from raw metataxonomic, metagenomic or metatranscriptomic sequences. To guide the analyses, several customizable workflows are included and are supported by tutorials and Galaxy interactive tours, which guide users through the analyses step by step. ASaiM is implemented as a Galaxy Docker flavour. It is scalable to thousands of datasets, but also can be used on a normal PC. The associated source code is available under Apache 2 license at https://github.com/ASaiM/framework and documentation can be found online (http://asaim.readthedocs.io) Conclusions Based on the Galaxy framework, ASaiM offers a sophisticated environment with a variety of tools, workflows, documentation and training to scientists working on complex microorganism communities. It makes analysis and exploration analyses of microbiota data easy, quick, transparent, reproducible and shareable.

First Authors:
Bérénice Batut

Correspondence Authors:
Bérénice Batut,Pierre Peyret

All Authors:
Bérénice Batut,Kévin Gravouil,Clémence Defois,Saskia Hiltemann,Jean-François Brugère,Eric Peyretaillade,Pierre Peyret

评论