贝叶斯线性混合模型具有多个随机效应,用于对高维多omics数据的预测分析
Yang Hai1,2, Jixiang Ma1, Kaixin Yang1
1Department of Health Statistics, Shanxi Medical University, Taiyuan, Shanxi Province 030000, China.
Bioinformatics (Oxford, England)
|October 26, 2023
概括
一个新的两步贝叶斯线性混合模型框架 (TBLMM) 增强了使用多omics数据的疾病风险预测. 这种方法有效地建模复杂的关系,并优于预测复杂特征的现有方法.
科学领域:
- 基因组学就是基因组学.
- 生物统计学 生物统计学
- 精准医学是一门精准的医学.
背景情况:
- 高度的多维数据为疾病风险预测提供了宝贵的资源.
- 在多学科数据中分析复杂的相互/内部关系带来了重大分析挑战.
研究的目的:
- 引入一个新的统计框架,以使用多omics数据准确预测疾病风险.
- 解决高维和复杂的多omics数据所带来的分析挑战.
主要方法:
- 提出了一个两步贝叶斯线性混合模型框架 (TBLMM).
- 采用了稀疏度回归和线性混合模型的混合混合模型,具有多个随机效应.
- 利用内核融合来模拟多omics数据中的非线性和相互作用效应.
- 实现了一个计算效率高的变量贝叶斯算法用于参数推理.
主要成果:
- TBLMM有效地模拟了多omics数据的预测效应,捕捉了复杂的关系.
- 该框架适应通过核融合的非线性和相互作用效应.
- 广泛的模拟和现实世界的数据分析 (阿尔茨海默病神经成像计划) 证明了TBLMM的卓越性能.
- 在预测复杂特征风险方面,TBLMM始终优于现有方法.
结论:
- TBLMM提供了一个强大而有效的框架,用于使用多omics数据进行疾病风险预测.
- 该方法处理复杂数据结构的能力为精准医学提供了进步.
- 针对TBLMM的R包在GitHub上公开提供,以获得更广泛的应用.
更多相关视频
08:51Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts
Published on: September 20, 2024
1.3K
12:39A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
Published on: December 10, 2012
11.4K
相关概念视频
01:23Mechanistic Models: Compartment Models in Individual and Population Analysis
45
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...
45
01:06Model Approaches for Pharmacokinetic Data: Distributed Parameter Models
74
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...
74
01:14Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches
141
Drug disposition in the body is a complex process and can be studied using two major approaches: the model and the model-independent approaches.
The model approach uses mathematical models to describe changes in drug concentration over time. Pharmacokinetic models help characterize drug behavior in patients, predict drug concentration in the body fluids, calculate optimum dosage regimens, and evaluate the risk of toxicity. However, ensuring that the model fits the experimental data accurately...
The model approach uses mathematical models to describe changes in drug concentration over time. Pharmacokinetic models help characterize drug behavior in patients, predict drug concentration in the body fluids, calculate optimum dosage regimens, and evaluate the risk of toxicity. However, ensuring that the model fits the experimental data accurately...
141
01:25Multiple Regression
3.0K
Multiple regression assesses a linear relationship between one response or dependent variable and two or more independent variables. It has many practical applications.
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
3.0K
01:14Multicompartment Models: Overview
151
Multicompartment models are mathematical constructs that depict how drugs are distributed and eliminated within the body. They segment the body into several compartments, symbolizing various physiological or anatomical areas connected through drug transfer processes such as absorption, metabolism, distribution, and elimination.
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...
151
01:24One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation
531
This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
On...
531