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This article will explain in detail what the odd ratio value means in the correlation analysis. The content of the article is of high quality, so the editor will share it with you for reference. I hope you will have a certain understanding of the relevant knowledge after reading this article.

In GWAS analysis, by using chi-square test and Fisher accurate test, we can analyze whether there is a correlation between snp locus and disease by judging whether the p value is significant or not. However, this is only a qualitative conclusion. If there is a correlation, how strong is the correlation?

Obviously, we need a quantitative indicator to describe the strength of the correlation. Similar to the correlation test, the p value can only show whether the two variables are related. As for the magnitude of the correlation, whether it is a positive correlation or a negative correlation, we still need to combine the correlation coefficient to judge. The "correlation coefficient" in correlation analysis corresponds to two commonly used statistics, risk ratio and odd ratio.

To explore the association between smoking and lung cancer, for example, the data format is as follows

Normal individuals with lung cancer smoke ab non-smoking cd

Risk ratio, also known as relative risk, abbreviated as RR, is often referred to as relative risk, which is the ratio of the incidence of the exposure group to that of the non-exposure group. For the above data, the calculation process of RR is as follows

The proportion of lung cancer in smoking group a / (a + b)

The proportion of lung cancer in non-smoking group c / (c + d)

RR = (a / (a + b)) / (c / (c + d))

The numerical value of RR directly reflects the incidence of exposure factors, RR > 1, the incidence in exposure group is higher than that in non-exposure group, indicating that there is a positive correlation between exposure factors and incidence, on the contrary, RR

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