I am trying to train a binary SVM classifier to identify a disease based on gene expression. So I have two classes: disease and heathly and their corresponding differential gene expression with respect to a control. For now, I considered each differential gene expression as feature of the SVM.
The gene expression is associated with a pvalue and some of them aren´t significant. None of the gene expression is consistently significant across all experiments, which means I can´t take out the non significant genes.
What can I do to take into account the differential expression? Would it make sense to add pvalues as features? Also, I thought about giving gene expression an outlier value.