ADAPT:通过汇集托比特模型来分析微生物群差异丰富度
Mukai Wang1, Simon Fontaine2, Hui Jiang1
1Department of Biostatistics, University of Michigan, Ann Arbor, 48109, MI, USA.
bioRxiv : the preprint server for biology
|May 27, 2024
概括
我们介绍了ADAPT,这是微生物群差异丰度分析的新方法. 它解决了诸如过度的零和组合性等挑战,提高了分析口腔微生物组数据的准确性和功率.
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.
- 统计遗传学 统计遗传学
背景情况:
- 微生物群差异丰度分析是复杂的,因为数据挑战,如过度的零和组合性.
- 现有的方法难以准确识别不同样本组的微生物种类.
研究的目的:
- 引入一种新的方法,即ADAPT,用于微生物群差异丰度分析.
- 克服现有方法在处理零数和组合性方面的局限性.
主要方法:
- ADAPT将零计数视为左边审查的观察.
- 它使用一种理论上合理的方法来选择参考分类群.
- 该方法使用合成数据和真实世界微生物群样本进行了验证.
主要成果:
- ADAPT展示了一致的错误发现率控制.
- 与现有方法相比,该方法显示出更高的统计能力.
- 对婴儿口腔微生物组数据的分析揭示了新的见解.
结论:
- ADAPT为微生物群差异丰度分析提供了一个强大的方法.
- 对婴儿口腔微生物组数据的应用揭示了早期儿童牙损伤相关性的新见解.
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