常用GWAS统计方法和模型简介

2018-01-24 本文已影响593人 rapunzel0103

本文是百迈客GWAS生物信息培训课程学习笔记第二篇，第一篇请参考GWAS基本分析内容

这里首先介绍了GWAS分析中常用的统计学概念：

1. 假设检验

零假设(H0,null hypothesis): 即原假设,指进行统计检验时预先建立的假设,一般是希望证明其错误的假设。GWAS中的H0是标记的回归系数为零, SNP对表型没有影响。

备择假设(H1，也叫对立假设，Alternative Hypothesis): 与原假设对立的假设，GWAS中的H1就是标记的回归系数不为零，SNP和表型相关。

doi: https://doi.org/10.1101/092106 Figure 1. Standard genetic association study applied to human blood pressure data. (a) The left SNP appears to be more strongly associated with blood pressure than the right SNP. (b) We test two hypotheses against each other to evaluate whether the association between a SNP and a phenotype is statistically significant. By default, a null hypothesis assumes that the SNP does not affect the phenotype. (c) If the data fits the alternative hypothesis beyond a certain threshold, the SNP is described as significantly associated with the phenotype.

图片来自参考文献 Review: Population Structure in Genetic Studies: Confounding Factors and Mixed Models

计算H0成立的概率，如果H0成立的概率很低，则拒绝H0，接受H1。但实际情况更复杂（下图b）

doi: https://doi.org/10.1101/092106 Figure 8. (a) The SNP and phenotype are independent under the null hypothesis (H0) and correlated under the alternative hypothesis (H1). (b) In the case of population structure, the structure will influence many SNPs and the phenotype. In this case, correlation between SNPs and the phenotype will be induced in both the null and alternate hypothesis.