I have a data frame each row represents a patient.
In there dataframe there are a list of SNPs, a list of lifestyle factors, and an outcome variable alzheimer's disease = 1 or 0.

I am using snp.logistic in the CGEN package to identify interactions between SNPs and between SNPs and lifestyle factors which are causative for alzheimer's disease in patients.

I have read the documentation and searched online.

Firstly, I am not sure how to set the main and interacting variables in the snp.logistic function. How do I know which variables need to be included in the model as main effects and which are interacting variables?

Secondly, when I change snp.var from one SNP to the other the p-value of main variables changes. Why would the predicted influence of main variables such as sex change because snp.var is changed? 

Thanks for your help!

The user needs to specify which variables will be main effects and which will be interacting with the snp. When you change the snp variable, the model changes, and you will get different p-values.