Hi 
I've done PCA for my gene expression data after DEG analysis, I can see that my case and control samples clustered distinctly but **I want to report a p.value for this result**, it worth to notice that I have the coordinate csv file that represents coordinates of samples from different phenotypes (case vs control).

Thanks in advance
What Nicolas says is true; however, there are indirect ways to derive a P value based on your PCA results.

#Buid a regression model
You can indirectly derive P values in your situation by building a binary logistic regression model using the PC1 (or PC2, PC3, ..., PCX) values to predict case/control status. From this, you should see a strong P value based on what you say.

    summary(glm(CaseControl ~ PC1))

#Correlation
For other type of variables, like continuous variables, you can simply run a correlation test between the continuous variable and the PC1 values, and derive a P value from this too (in R, use `cor.test()`)
