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使用R进行微生物组分析的综合指南.

Joseph Boctor1, Mariam Oweda2, Mohamed El-Hadidi3

  • 1Biotechnology Program, American University in Cairo (AUC), Cairo, Egypt.

Methods in molecular biology (Clifton, N.J.)
|May 31, 2023
PubMed
概括
此摘要是机器生成的。

本指南简化了使用R的微生物组数据分析,详细介绍了像phyloseq,DADA2和Metacoder这样的必不可少的R包,以实现高效的数据集成和探索.

关键词:
DADA2 DADA2 的意思是什么?这是一个巨大的MegaRR.微生物组数据分析分析R 套餐 R 套餐是一套套套餐.微生物组 探索者 探索者基因组分类 (phyloseq) 是指一个基因组.

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科学领域:

  • 微生物学 微生物学
  • 生物信息学是一种生物信息学.
  • 计算生物学 计算生物学

背景情况:

  • 微生物组研究产生复杂的数据集,需要专门的分析工具.
  • 现有的微生物组分析的R包是众多的,导致需要综合指导.

研究的目的:

  • 为微生物组数据分析提供全面,用户友好的关键R包指南.
  • 为研究人员简化微生物组数据整合和分析的过程.

主要方法:

  • 一个逐步的教程方法,侧重于五个突出的R包:phyloseq,MegaR,DADA2,Metacoder和microbiomeExplorer.
  • 使用这些选定的工具展示高效的数据集成和分析工作流程.

主要成果:

  • 详细剖析每个R.包的功能和应用.
  • 插图示例展示了这些工具在微生物组数据分析中的实际好处.

结论:

  • 选择的R包为微生物组数据分析提供了高效率和显著的好处.
  • 这份综合指南是微生物组生物信息学研究人员的宝贵资源.