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.
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.
2. 两类错误与统计功效
Type I error (I类错误): 拒绝真实的H0，即假阳性，概率α为显著性水平；
Type II error (I类错误): 接受错误的H0，即假阴性，概率为β；
功效(power): 拒绝错误H0的概率 1-β
From Zhiwu Zhang's slides http://zzlab.net/StaGen/2017
