探索基因-环境和基因-基因相互作用的贝叶斯式方法:综合性审查
N A Sun1, Y U Wang1, Jiadong Chu1
1Department of Epidemiology and Biostatistics, School of Public Health, Medical College of Soochow University, Suzhou, P.R. China.
Cancer genomics & proteomics
|November 30, 2023
概括
贝叶斯模型通过整合基因-基因和基因-环境相互作用来解决复杂疾病中遗传性缺失的问题. 这些先进的方法提高了预测的准确性,并使用omics数据揭示了疾病机制.
科学领域:
- 遗传学 是一个遗传学.
- 生物统计学 生物统计学
- 计算生物学 计算生物学
背景情况:
- 高通量omics数据生成支持精准医学.
- 在复杂疾病中遗传性缺失的挑战仍然存在.
- 了解基因架构需要结合基因相互作用.
研究的目的:
- 审查贝叶斯的方法来识别和估计遗传相互作用.
- 突出基因环境 (G×E) 和基因基因 (G×G) 相互作用的模型.
- 讨论这些模型在复杂疾病研究中的应用.
主要方法:
- 对基因分析的贝叶斯统计模型的审查.
- 专注于包含主要效应和相互作用 (M-I) 的模型.
- 包括基于单核酸多态 (SNP) 的研究和机器学习-贝叶斯方法.
主要成果:
- 贝叶斯模型提高了识别遗传效应和相互作用的准确性.
- 基于效应遗传和基于组的原则的模型提供了灵活性.
- 机器学习-贝叶斯式方法显示出高预测准确度.
结论:
- 贝叶斯方法为剖析复杂疾病遗传学提供了强大的工具.
- 这些方法提高了对疾病机制和生物标志物发现的理解.
- 审查的模型有助于改进精准医学中的预后预测.
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