Hi, I have an statistics doubt that probably is basic but I'm not clear about that.
I'm trying to find genes with differential expression, which RNA levels depend on 3 experimental factors (factor A and B with 2 levels each and a factor C with 3 levels). We've done a 3-way ANOVA from the log2(normalized counts) from different libraries and also a linear regression to look for genes with a p<0.05 for the intersection of the 3 factors.
I'm not sure if it is correct to do a linear regression or an ANOVA, considering my experimental design. I've observed that the number of genes with a significant p-value for the triple intersection is very lower when we apply the linear regression.
Does anyone can help me if it is a correct statistical analysis? I really don't understand very well the difference between ANOVA and linear regression, but I've seen that linear regression is always used in 2-way ANOVA for RNA seq data.
Any help is welcome.
Thanks in advance.