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Updated: May 25, 2025

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分析微生物组数据与分类错误分类,使用零膨胀的迪里克莱特多项式模型

Matthew D Koslovsky1

  • 1Department of Statistics, Colorado State University, Fort Collins, CO, USA. matt.koslovsky@colostate.edu.

BMC bioinformatics
|February 27, 2025
PubMed
概括

这项研究引入了一种新的统计模型,用于分析人类微生物群数据,计算过多的零和识别微生物的潜在错误. 该模型提高了准确性,并揭示了健康和肥胖儿童之间的肠道微生物差异.

关键词:
构成性的组成.高维的高维空间多变量计数数据多变量计数数据肥胖问题 肥胖问题

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Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
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