Question: DESeq2 with interest only for 1 gene
0
gravatar for fischer87
3.3 years ago by
fischer870
fischer870 wrote:

Hi everybody,
for a research, I  measured the expression levels of about 150 genes in 30 patients. Now, I'm interested to see if there is a difference, among three groups of these patients, in the expression levels of a particular gene (only one).

Could I use DESeq2 to do that?
The problem is that I can't use a statistical model directly on the raw data, then I would firstly normalize the raw data of this gene, secondly I want to do a correct statistical test.

I thought to use DEseq2 to normalize my gene using all the 150 genes, then do DESeq2 analysis and finally extract only the result for that gene (ignoring the others).

In your opinion, is it a correct procedures to do?

Thank you very much for your help, and sorry if my english is not correct, but I do not speak it very well.

Thank you again!
Bye

 

ADD COMMENTlink modified 3.3 years ago • written 3.3 years ago by fischer870
Answer: DESeq2 with interest only for 1 gene
0
gravatar for Michael Love
3.3 years ago by
Michael Love25k
United States
Michael Love25k wrote:

Are there genes in the 150 that you expect to be not differentially expressed? If not, was there any external control (spike-in) included in the sequencing of each sample?

ADD COMMENTlink written 3.3 years ago by Michael Love25k
Answer: DESeq2 with interest only for 1 gene
0
gravatar for fischer87
3.3 years ago by
fischer870
fischer870 wrote:

Yes, I expect that all the other 149 genes are not differentially expressed. I thought to leave all the 150 genes in the analysis in order to correctly normalize my gene of interest.

Sorry, how can I see the normalized counts? Is it correct to use the command:

dds <- DESeqDataSetFromMatrix(countData=countD, colData=colData, design=~condition)

NormData <- counts(dds, normalized=TRUE)

 

Thank you very much!

ADD COMMENTlink written 3.3 years ago by fischer870

(Note that if you are replying to my answer, you can use the Add Comment/Reply buttons instead of the Add Answer. Add Answer is for answering the top post, which is your own.(

Then you can just run DESeq() as normal. The 149 other genes should be sufficient to normalize the data, because the library size estimation is robust to a fraction of DE genes (just not when DE is the majority). I'd recommend using fitType="mean" when you have ~100 rows instead of the typical 1000s of rows in the DESeqDataSet.

Yes that is how you get normalized counts.

ADD REPLYlink written 3.3 years ago by Michael Love25k
Answer: DESeq2 with interest only for 1 gene
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gravatar for jshouse
3.3 years ago by
jshouse10
jshouse10 wrote:

@fischer87  That is how I get normalized counts from DESeq2.

ADD COMMENTlink written 3.3 years ago by jshouse10
Answer: DESeq2 with interest only for 1 gene
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gravatar for fischer87
3.3 years ago by
fischer870
fischer870 wrote:

Thank you very much!!

ADD COMMENTlink written 3.3 years ago by fischer870

For future reference: these type of responses should be added as a comment to the answer you are replying to, which you can do by clicking on the big "ADD COMMENT" link below the text of every answer.

ADD REPLYlink written 3.3 years ago by Steve Lianoglou12k

Sorry!

Thank you very much for your advice, surely in the future i will do that!

Bye

ADD REPLYlink written 3.3 years ago by fischer870
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