I was wondering what statistical test does DEseq use for estimating the differential expression values is it a chi-sq. / Fisher exact test or some other?
Where to start.... The simplest answer is "some other"
If you are not satisfied with this answer, I would first try reading the paper though it might be hard to understand so it could be easier to start with a review.
You can think of what DESeq does as kind of like a modified t-test on counts but the counts need to be normalized before you can use them. Istvan's answer here provides a great starting point as well as this post.
Assuming you have a good understanding of NGS count data, you should also learn how linear modeling works. The user guide here is great for walking a beginner through how differential expression analysis works. edgeR is a tool similar to DESeq though there are some differences.
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That's fine! I did but I am not a statistics person and was a bit confused!
I am actually using the Jmp Genomics to analyze a KDMM normalized data set, but along the way also performed it with DESeq, I read the paper but wasn't that clear on the exact DE estimation method of DESeq. This should be helpful thanks ...
I just dug through and saw your post: DESeq statistical test. I agree with what @Devon Ryan says and I'm not quite sure why you opted for KDMM (other than maybe its an option in Jmp?). You might also want to have a look at this thread