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微生物组数据的纵向分析中的方法考虑:全面审查
Ruiqi Lyu1, Yixiang Qu2, Kimon Divaris3,4
1Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
Genes
|January 23, 2024
概括
分析时间序列微生物组数据对于理解健康和疾病动态至关重要. 本综述比较了分析纵向微生物组数据的方法,进一步了解了宿主-微生物组关系.
科学领域:
- 微生物组研究的研究.
- 计算生物学是一种计算生物学.
- 数据科学是数据科学.
背景情况:
- 生物过程是动态的,随着时间的推移,最好理解.
- 纵向微生物组数据分析带来了独特的挑战.
- 了解宿主微生物组的动态是健康和疾病的关键.
研究的目的:
- 审查和比较时间序列微生物组数据分析的方法.
- 为了应对处理纵向微生物组数据的挑战.
- 突出计算工具在微生物组研究中的重要性.
主要方法:
- 关于微生物组时间序列分析的现有文献的全面审查.
- 预处理和下游分析方法的比较.
- 讨论差异分析,聚类,网络推理和特征分类.
主要成果:
- 在时间序列微生物组数据分析中发现了挑战.
- 对比了各种可用的计算方法和方法.
- 强调了适当的分析工具的实用性.
结论:
- 适当处理纵向微生物群数据可以提供有关微生物角色和相互作用的见解.
- 计算工具对于理解动态宿主-微生物组关系至关重要.
- 这种分析有助于通过微生物组动态来了解健康,疾病和发育阶段.
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