I am doing DEG analysis between two sample (Normal vs Treated) without replicates using edgeR. I know there is no significance of analysis without replicates, but i have no other choice.

```
library(edgeR)
data = read.table("MYFILE-counts.txt", header=T, row.names=1, com='')
bcv <- 0.2
counts <- data
y <- DGEList(counts=counts, group=1:2)
et <- exactTest(y, dispersion=bcv^2)
```

The count matrix was generated by Corset, which gives the count matrix in Poisson distribution while i am applying exactTest which takes count matrix as negative binomial distribution. Should i carry on with this analysis only or use another test equivalent to exactTest for Poisson distributed count matrix? If there is any other test then what it is? What value of dispersion should be taken according to the data-set?

my variable:

```
>y
An object of class "DGEList"
$counts
Normal.bam Treated.bam
Cluster-0.0 0 50
Cluster-1.0 0 25
Cluster-2.0 0 16
Cluster-2.1 0 8
Cluster-3.0 0 15
... more rows ...
$samples group lib.size norm.factors
Normal.bam 1 3.22e+07 1
Treated.bam 2 1.05e+08 1
>et
An object of class "DGEExact"
$table
logFC logCPM PValue
Cluster-0.0 8.03 -1.58 4.06e-05
Cluster-1.0 7.04 -2.39 2.13e-03
Cluster-2.0 6.40 -2.89 3.49e-02
Cluster-2.1 5.42 -3.58 7.51e-02
Cluster-3.0 6.31 -2.95 3.49e-02
202654 more rows ...
$comparison
[1] "1" "2"
$genes
NULL
```

For Gordon Smyth's expert answer see: https://support.bioconductor.org/p/124721/