相关实验视频

Updated: Jun 24, 2025

Assisted Selection of Biomarkers by Linear Discriminant Analysis Effect Size LEfSe in Microbiome Data
04:57

Assisted Selection of Biomarkers by Linear Discriminant Analysis Effect Size LEfSe in Microbiome Data

Published on: May 16, 2022

15.7K

一个基于GLM的零膨胀通用Poisson因子模型,用于分析微生物组数据

Jinling Chi1, Jimin Ye1, Ying Zhou2

  • 1School of Mathematics and Statistics, Xidian University, Xi'an, China.

Frontiers in microbiology
|June 14, 2024
PubMed
概括

我们开发了一个新的统计模型来分析肠道微生物组数据,解决诸如过多的零和过度分散等挑战. 这种方法提高了我们对肠道微生物与肥胖等疾病之间的联系的理解.

关键词:
在 GLM 里面.这是一个ZIGP模型.在因子分析的过程中,因素分析.微生物组数据的数据零通货膨胀 没有通货膨胀

更多相关视频

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing11:22

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing

Published on: October 15, 2019

27.9K
Analysis of Fecal Microbiota Dynamics in Lupus-Prone Mice Using a Simple, Cost-Effective DNA Isolation Method05:28

Analysis of Fecal Microbiota Dynamics in Lupus-Prone Mice Using a Simple, Cost-Effective DNA Isolation Method

Published on: May 2, 2022

2.1K

相关概念视频

Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

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...
36