Hi,

We have run a pilot RNA-Seq study with one sample per condition, this is just a test run. I understand there is no valid statistical test in this case, however just curious to obtain differential expression through edgeR package in R assuming dispersion = 0.4 for the human data. I have a normal (baseline) sample followed by 5 different samples. When I run the edgeR package, I want to indicate my normal sample (as baseline), however, I am unsure what sample here is taken as a baseline for calculation of fold change. 

**FC calculation**

>     FC = Normal/Test_1 (OR) 
>     FC = Test_1/Normal

**Samples**

>     Normal (baseline) = Normal
>     Test (Treated) = Test_1
> 


**Data**

    dput(df_data)
    structure(list(Normal = c(0L, 184L, 60L, 0L, 7L, 0L, 87L, 0L, 
    0L, 21L, 193L, 29L, 0L, 0L, 3L, 50L), Test_1 = c(0, 140.5, 64, 
    0, 4, 0, 83, 0, 1, 51.5, 199, 25, 0, 0, 5, 62)), class = "data.frame", row.names = c("Gene1", 
    "Gene2", "Gene3", "Gene4", "Gene5", "Gene6", "Gene7", "Gene8", 
    "Gene9", "Gene10", "Gene11", "Gene12", "Gene13", "Gene14", "Gene15", 
    "Gene16"))
    
    
    dput(df_metadata)
    structure(list(SampleID = c("xxxx1", "xxxx2"), CoreLabID = c("Normal", 
    "Test_1")), class = "data.frame", row.names = c("Normal", "Test_1"
    ))

**Here is the code that I am running**

    bcv <- 0.4
    y <- DGEList(counts=df_data, group=df_metadata$CoreLabID)
    et <- exactTest(y, dispersion=bcv^2)

>     View(et$table)
>     structure(list(logFC = c(0, -0.67280976110796, -0.190706878123648, 
>     0, -1.06592239047733, 0), logCPM = c(0.456451013758882, 6.84518828528986, 
>     5.46338499556895, 0.456451013758882, 2.37389406911164, 0.456451013758882
>     ), PValue = c(1, 0.433579402199822, 0.851984371429117, 1, 0.542580328250669, 
>     1)), row.names = c("Gene1", "Gene2", "Gene3", "Gene4", "Gene5", 
>     "Gene6"), class = "data.frame")
> 
>     View(et$comparison)
>     c("Test_1", "Normal")

Thank you,

Toufiq
edgeR has compared `Test_1` to `Normal` so, yes, the normal sample has been taken as the baseline. `et$comparison` records the numerator and denominator for the fold-change respectively.

You can find this out for yourself by reading the help page for `exactTest`, `help(exactTest)`. See the documentation for the `pair` argument.

If you use the standard edgeR pipeline
```
topTags(et)
```
then the results will be presented in a easy to read form and the output will tell you which sample has been compared to which.
