baseMean differencies according to the model
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jrivera • 0
@jrivera-11162
Last seen 8.4 years ago

Hello!

I would like to understand how does DESeq to compute the baseMean values for each model.

I have tho models:

MODEL A: where design = ~ V1

MODEL B: where design = ~ V2 + V1

 

When the results matrix appers for each model, there are some bacterias for which baseMean value change between them and the rest arte still the same. Why these changes, and why not in every bacteria?

 

Tank you!

Deseq2 model • 1.1k views
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@mikelove
Last seen 22 hours ago
United States

If some very high outlier counts are replaced by DESeq() then the base mean has to be re-estimated, so as to not be influenced by those very high counts. The outlier replacement procedure depends on the experimental design.

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jrivera • 0
@jrivera-11162
Last seen 8.4 years ago

Thank you!

Where can I see which individuals have changed their value for certain bacteria?

Following the manual and running until DESeq() function with both designs, counts() of the previous object are the same for both MODEL A and MODEL B.

So, I think that outliers should be replaced in res() function; isn't it?

 

 

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I'm adding a comment to start a threaded discussion... not that the ADD YOUR ANSWER is for replying to the top post (your original question).

If you take a look at ?DESeq you have information about this, under Details, the paragraph starting with "The argument minReplicatesForReplace is used to decide..."

If you prefer, you can turn off the outlier replacement using minReplicatesForReplace=Inf for DESeq() and turn off filtering with cooksCutoff=FALSE in results() and then examine the genes with high mcols(dds)$maxCooks by eye. These procedures were designed using "standard" RNA-seq datasets and manual inspection may perform better for other types of datasets.

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