Before running any RNA-seq data analysis packages, I want to do statistical test for my gene expression data. I have 4 replicates for two treatment (r and s). As RNA-seq data have -ve bionomial distribution. Does it make any sense if i do gene wise paired t-test, so that i can get p-values for each gene.

```
r1 r2 r2 r4 s1 s2 s3 s4
gene1 569 257 301 446 259 289 835 414
gene2 24 1 28 26 15 1 51 36
.
.
```

The following lines (this is not a code) is what i would like to execute :

```
gene1 :paired t test[(569 257 301 446) Vs (259 289 835 414)]
gene2 :paired t test [(24 1 28 26) Vs (15 1 51 36)]
```

This is just for getting an idea about the data values per conditions not for actual analysis. Can i do paired t-test in this way? also does the above calculation make any sense on getting p-value per gene ? Seeking suggetions in this context.

Thanks Nicobxl, I can use edgeR and DESeq. Actually, While browsing through microarray data analysis, To do t-test came in my mind that will help me to understand the usage of t-test and other statistical test in gene expression analysis. The above excercise is just for learning concepts. Thus i want to know does it make any sense with context to RNA-seq data ( Count data : Bam converted to counts by HTSeq package).