EdgeR analysis with no replicates - how to run exact test with set dispersion value?
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bertb • 0
@bertb-18667
Last seen 2.1 years ago
Canada

Hello,

I am trying to run a differential analysis with EdgeR for 2 RNAseq samples, with only one condition (1 treatment, 1 control), and I only have 1 replicate of each, which I know is far from ideal.

Having reviewed the user manual, I've decided to use option 2 for this scenario (on pg. 23), where I will choose a reasonable BCV, and use that to run the exact test.

Unfortunately, I'm having a difficult time understanding what commands to run in order to do this, despite the example detailed in the manual.

After normalizing my samples, my effective libraries are as follows:

> ynorm$samples
           group lib.size norm.factors
UWN_t2.bam     1  6411675    1.0307067
UMN_t2.bam     1  9047788    0.9702081

from reviewing the manual, I know I need to now set the BCV (with my chosen value of 0.2)

>bcv <- 0.2

but after that I don't know how to create a new DGEList which incorporates this new value, in order to run the exact test, since in the provided example there are some settings included that I cannot understand (size, mu, etc.).

Any advice would be greatly appreciated! Thank you,

edgeR • 2.5k views
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@james-w-macdonald-5106
Last seen 15 hours ago
United States

The part you don't understand is just the creation of simulated data. You already have a DGEList called ynorm, so you don't need to generate any data. Instead you just go to the next step, which is fitting the exact test.

et <- exactTest(ynorm, dispersion = bcv^2)
topTags(et)
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Entering edit mode

I see - thank you for clarifying!

when I run the test as you suggested however, I receive the following error:

> et <- exactTest(ynorm, dispersion = bcv^2)
Error in exactTest(ynorm, dispersion = bcv^2) : 
  At least one element of given pair is not a group.
 Groups are: 1

Do I need to put each sample in a different group?

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1
Entering edit mode

Yes. You should have included a group = 1:2 in your call to DGEList when you first made it.

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