一个贝叶斯半参数混合模型,用于集群零膨胀微生物组数据
Suppapat Korsurat1, Matthew D Koslovsky1
1Department of Statistics, Colorado State University, Fort Collins, CO, 80523, United States.
Biometrics
|September 23, 2025
概括
这项研究引入了一种新的贝叶斯模型来分析人类微生物组数据. 该方法有效地识别了微生物组成中的子组,这对于了解健康和疾病联系至关重要.
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.
- 统计建模 统计建模
背景情况:
- 人类微生物组研究旨在将微生物组成与健康和疾病联系起来.
- 现有的集群方法与复杂的零膨胀微生物组数据作斗争,并且通常需要预先指定集群的数量.
- 这种限制可以在识别有意义的子组时引入偏见.
研究的目的:
- 为微生物组数据开发一个新的贝叶斯半参数混合模型框架.
- 同时确定集群的数量并将个人分配给它们.
- 为应对零通胀和微生物组数据的组成性质所带来的挑战.
主要方法:
- 开发了一个贝叶斯半参数混合模型.
- 该模型是为零膨胀的多变量组成计数数据设计的.
- 通过模拟来评估性能,并应用于现实世界肠道微生物群数据集.
主要成果:
- 拟议的贝叶斯框架有效地识别了微生物组数据中的子组.
- 该方法准确地确定了集群的数量,没有事先的假设.
- 与现有方法相比,模拟证实了较优的集群性能,特别是使用零膨胀数据.
结论:
- 新的贝叶斯建模框架为微生物组子组发现提供了一个强大的方法.
- 准确识别微生物子组可以促进对肠道微生物组成的理解,例如在腹等疾病中.
- 这种方法通过适应数据复杂性和同时学习集群数量来改善推断.
相关概念视频
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models
218
Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
218
Cluster Sampling Method
13.9K
Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
13.9K
Model Approaches for Pharmacokinetic Data: Compartment Models
496
Compartmental analysis is a widely adopted approach to characterizing drug pharmacokinetics. It uses compartment models that conceptualize the body as a collection of reversibly communicating compartments, each representing a group of tissues exhibiting similar drug distribution characteristics. The movement rate of the drug between these compartments is typically described by first-order kinetics.
Two primary types of compartment models are recognized: mammillary and catenary. The more...
Two primary types of compartment models are recognized: mammillary and catenary. The more...
496
Mechanistic Models: Compartment Models in Individual and Population Analysis
221
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...
221
Distributions to Estimate Population Parameter
5.0K
The accurate values of population parameters such as population proportion, population mean, and population standard deviation (or variance) are usually unknown. These are fixed values that can only be estimated from the data collected from the samples. The estimates of each of these parameters are sample proportion, the sample mean, and sample standard deviation (or variance). To obtain the values of these sample statistics, data are required that have particular distribution and central...
5.0K
Clearance Models: Noncompartmental Models
227
Clearance is a pharmacokinetic parameter traditionally defined by compartment models, signifying the rate at which a drug is expelled from the body. However, a noncompartmental model offers an alternative method for assessing clearance, primarily employing empirical data obtained after administering a single drug dose.
The noncompartmental approach capitalizes on extensive sampling data, correlating the volume of distribution to systemic exposure and the administered dosage. This method enables...
The noncompartmental approach capitalizes on extensive sampling data, correlating the volume of distribution to systemic exposure and the administered dosage. This method enables...
227


