Entering edit mode
7.4 years ago
ashkan
▴
160
I have 4 samples and got RNA-seq data from all 4 samples and count the read count for all of them. then I got the genes involved in cell cycle and got the read counts only for those genes. then to compare samples 1 and 2 I divided the read count per gene from sample 2 by that of sample one. I did the same to compare 3 and 4. and got the log value of them. then I made a box plot for both comparisons. now I am going to compare the mentioned comparisons and get a P-Value for that to see whether these 2 comparisons are different or not. but the problem is that I don't know which statistical test needs to be done.
do you guys know which statistical test is what I need? and how to do that?
So you are basically interested in differentially expressed genes, right? You may have a look at established tools, such as DESeq, which are specifically designed for that kind of purpose plus provide functions for data normalization.
Don't forget to follow up on your previous question. Would be a nice habit to first finish those threads before opening a new question.
And please please, don't use your own "statistical" methods to do common tasks such as differential expression analysis of RNA-seq data. Clever solutions are available such as DESeq2, edgeR, limma-voom, kallisto-sleuth,...