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预处理和规范化代谢学数据,用于统计分析.

Jun Sun1, Yinglin Xia2

  • 1Division of Gastroenterology and Hepatology, Department of Medicine, Department of Microbiology/Immunology, UIC Cancer Center, University of Illinois Chicago, Jesse Brown VA Medical Center Chicago (537), Chicago, IL 60612, USA.

Genes & diseases
|February 1, 2024
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概括
此摘要是机器生成的。

代谢学,研究小分子,需要数据预处理进行分析. 本综述涵盖了质谱和核磁共振数据的方法,这些方法对于精密医学中的微生物组和代谢组研究至关重要.

关键词:
数据中心化和扩展.数据规范化的数据规范化.数据转换 数据转换基于MS的数据预处理.缺失的值是指缺失的值.进行NMR数据预处理.异常价值观 异常价值观是指异常价值观.预加工/预处理

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科学领域:

  • 生物化学 生物化学
  • 生物信息学是一种生物信息学.
  • 系统生物学 系统生物学

背景情况:

  • 代谢学研究生物样本中的小分子,为精准医学提供了洞察力.
  • 将代谢学与微生物组数据相结合,揭示了微生物在健康和疾病中的作用.
  • 代谢学数据的复杂性需要在分析之前进行强大的预处理和规范化.

研究的目的:

  • 对代谢学数据的预处理和数据处理方法进行全面审查.
  • 讨论基于质谱 (MS) 和核磁共振 (NMR) 的代谢学技术.
  • 突出处理缺失值,异常值,规范化,缩放和转换的考虑因素.

主要方法:

  • 对已建立和新兴的代谢学数据预处理方法的审查.
  • 对MS和NMR数据的技术进行比较分析.
  • 讨论数据归算,异常值检测,规范化和转换的策略.

主要成果:

  • 详细概述各种预加工技术,包括它们的优点和局限性.
  • 根据生物背景,数据特征和统计分析选择适当方法的指导.
  • 探索预处理对微生物组和代谢组整合研究的影响.

结论:

  • 适当的预处理对于准确的代谢学数据分析至关重要.
  • 方法选择取决于具体的研究问题和数据属性.
  • 有效的预处理增强了代谢学在精密医学和微生物组研究中的实用性.