Hello all. Merry Christmas and happy holidays!
I am currently conducting a study and was hoping to get some advice on my model for differential expression. Currently, I have the following data:
Sample || Sex || Age || TissueType || Individual || Diseased ID1 || Male || 70 || Hemisphere || Individual 1 || Affected ID2 || Male || 70 || Cortex || Individual 1 || Affected ID3 || Female || 80 || Hemisphere || Individual 2 || Unaffected ID4 || Female || 80 || Cortex || Individual 2 || Unaffected ID5 || Male || 100 || Hemisphere || Individual 3 || Affected
Currently, I have the following model for my sleuth LRT test because I am interested in whether across these two different regions of the brain, are there differentially expressed genes in cases VS controls. I was reading about nested models and was wondering if the following model makes sense:
Full Model: ~ Diseased + Sex + Age + Sex:Age + Sex:Diseased + Age:Diseased + Diseased*TissueType + Diseased*Individual
Reduced Model: Sex + Age + Sex:Age + Sex:Diseased + Age:Diseased + Diseased*TissueType + Diseased*Individual
I tested this and found 6000 genes with a p-value of 0, and realized that there is something wrong haha. I'm also not sure whether to include additively + TissueType and + Individual. I would really appreciate any advice. Thank you so much!