Why the t-test for a specific gene shows different value compared to differential analysis? I have RNA-Seq data for LUNG cancer. 370 tumor and 50 Normal. For differential analysis initially I did some filtering and kept approx. 19k genes for further analysis. I used edgeR.

With a FC > or &lt; 2 and FDR &lt; 0.05
tr &lt;- glmTreat(fit, contrast=contrast.matrix, lfc = log2(2))
I got approx 3000 differentially expressed genes. 

Among the 3000 differentially expressed genes I'm interested in a gene OIT3.

GeneSymbol  logFC    unshrunk.logFC   logCPM          PValue      FDR
  OIT3  2.156487448  2.171599487    -0.437234244    0.000701037 0.005304312


I see the above gene OIT3 is Upregulated. Why I see logCPM with negative value?

And I plotted the logCPM expression of the above gene and did a t-test which gave pvalue 0.1 which means not significant.



1) I see the gene is differentially expressed with Differential analysis using edgeR. Why I see logCPM with negative value?

2) With t-test why it is not significant?
There is no reason your t-test should reproduce edgeR. In fact, edgeR exists because t-test is inappropriate.

edgeR does the tests by pooling information from all genes, because with the low number of replicates your t-test doesn't give sufficient statistical power.

What you need to do is: check visually your gene and make a decision yourself based on graphical results and edgeR results if your gene shows biologically significant.