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The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.
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用R进行生物功能类丰富分析,用于长板科学家的注释教程.

Kejin Hu1

  • 1Department of Microbiology, Immunology and Genetics, College of Biomedical and Translational Sciences, University of North Texas Health Science Center, Fort Worth, TX 76107, USA.

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概括

本教程提供了生物功能类丰富分析 (FunCEA) 的R脚本,以识别与生物条件相关的基因组. 它详细介绍了使用基因本体学,KEGG和反应体数据库的过度表示分析和功能类评分等方法.

关键词:
基因和基因组的京都百科全书 (KEGG)分类网络图片 (cnetplot) 网络图片集群Profiler 描述器 集群Profiler 描述器丰富的可视化 丰富的可视化函数类丰富分析 (FunCEA) 是一种功能类丰富分析.功能类评分 (FCS) 是一种功能类评分.基因本体学 (GO) 是一种基因本体学.基因组丰富分析 (GSEA) 基因组丰富分析过度代表性分析 (ORA)路径丰富分析的分析方法

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科学领域:

  • 生物信息学是一种生物信息学.
  • 计算生物学 计算生物学
  • 基因组学就是基因组学.

背景情况:

  • 高通量测序产生基因列表,需要方法来识别功能相关的基因组.
  • 生物功能类丰富分析 (FunCEA) 解决了将基因表达变化与特定的生物或生物医学条件联系在一起的需求.

研究的目的:

  • 为实验室科学家提供FunCEA的可访问的R协议,包括数据处理和可视化.
  • 详细介绍两个流行的FunCEA方法:过度表示分析 (ORA) 和功能类评分 (FCS).

主要方法:

  • 使用R,一个强大的统计计算和图形平台.
  • 使用基因本体学 (GO),基因和基因组的京都百科全书 (KEGG) 和反应体知识数据库来实现FunCEA.
  • 为丰富分析,数据处理和可视化提供详细的R脚本.

主要成果:

  • 在R环境中使用ORA和FCS方法演示FunCEA.
  • 包括R代码用于各种可视化:点图,术语基因网络图,丰富图,图和GSEA图.
  • 突出了用于访问KEGG数据库的"集群Profiler"包的实用性.

结论:

  • 这个R教程为研究人员提供了一个全面的指南,可以在没有商业软件的情况下执行FunCEA.
  • 提供的脚本和解释有助于对不同生物条件的基因丰富结果进行解释.
  • 该研究强调了R的力量,以及生物医学研究中可复制和可访问的功能丰富分析的特定包.