Question: Using the "listValues" argument of DESEQ in multiple group comparisons
0
gravatar for mm2489
2.1 years ago by
mm24890
United States
mm24890 wrote:

I'm using deseq2 to find differentially expressed genes across 7 different cancer types. My goal is to obtain a list of genes differentially expressed when comparing each cancer to all others. For instance, comparing BRCA to all others. My question is about setting the "listValues" argument in the results() function.  I know the default is set to c(1,-1), but since I want to compare 1 group to 6 groups for each contrast, should I change that to c(1,-1/6)? Example code given below. Also, is this the right way of running deseq for this kind of analysis or should I stick to pairwise comparisons (e.g. BRCA vs. COAD only)?

 

tissue <- c(rep("BRCA",1222), rep("COAD",521), rep("LIHC",424), rep("LUAD",594), rep("LUSC",551), rep("0V",379), rep("PAAD",182))

sampleTable <- data.frame(sampleName = sampleFiles,

                          fileName = sampleFiles,

                          tissue = tissue)

ddsHTSeq <- DESeqDataSetFromHTSeqCount(sampleTable = sampleTable,

                              design= ~ tissue)

ddsHTSeq <- ddsHTSeq[ rowSums(counts(ddsHTSeq)) > 1, ]

register(MulticoreParam(20))

dds <- DESeq(ddsHTSeq, parallel=TRUE)

res <- results(dds, parallel=TRUE)

results(dds, contrast = list("BRCA", c("LUAD","LUSC", "LIHC", "OV", "COAD", "PAAD")), 

        listValues=c(1, -1))

 

deseq2 • 812 views
ADD COMMENTlink modified 2.1 years ago by Michael Love22k • written 2.1 years ago by mm24890
Answer: Using the "listValues" argument of DESEQ in multiple group comparisons
2
gravatar for Michael Love
2.1 years ago by
Michael Love22k
United States
Michael Love22k wrote:

Yes, you would use c(1,-1/6).

That gives you a comparison of the one group against an average of the other groups in terms of log2 fold changes.

ADD COMMENTlink written 2.1 years ago by Michael Love22k

Thanks exactly what i was looking for!

ADD REPLYlink written 18 months ago by Jeff Granja10

Dear Michael,

With reference to this post and the one at: A: lfcshrink in DESeq2 with grouping variable
I want to understand if what I did is correct.

Here is the condition_df:
                  disease_state condition
HC1_BND       Healthy       BND
HC1_MN        Healthy        MN
HC2_BND       Healthy       BND
HC2_MN        Healthy        MN
HC3_BND       Healthy       BND
HC3_MN        Healthy        MN
HC4_BND       Healthy       BND
HC4_MN        Healthy        MN
S1_BND       Diseased       BND
S1_MN        Diseased        MN
S2_BND       Diseased       BND
S2_MN        Diseased        MN
S3_BND       Diseased       BND
S3_MN        Diseased        MN
S4_BND       Diseased       BND
S4_MN        Diseased        MN

Now, my goal is to find genes that are different for "Diseased and BND" category as opposed to all others. To accomplish that, I did the following:
dds <- DESeqDataSetFromMatrix(countData = htseq_counts[rownames(condition_df)],
                                                       colData = condition_df,
                                                       design =  ~ disease_state + condition + disease_state:condition)
dds <- DESeq(dds)

 

Running the following command gives me the bulleted list below

resultsNames(dds)

  • "Intercept"  
  • "disease_state_Healthy_vs_Diseased"
  • "condition_MN_vs_BND"              
  • "disease_stateHealthy.conditionMN" 

Then I did this:
result_A <- results(dds, contrast=list( c("disease_state_Healthy_vs_Diseased","condition_MN_vs_BND") ))

Running "results" function gave me a few (30) genes that clustered well for Diseased and BND option along with other(50) genes that clustered for other categories.

Now my questions for you are:

  1. Is my understanding of the above method correct?
  2. I am not quite sure if I understand how the resultsNames are generated and why isn't there a combination such as: disease_stateDiseased.conditionBND - as this is what I would be interested in; or how could I get that?
  3. Is there a better way to just get the genes that are differentially expressed in the Diseased_BND category as opposed to any other?

Thanks much,

Ashu


 

 

 

 

 

 

 

 

 

ADD REPLYlink written 6 months ago by Ashu10

Would you mind posting this as a new question, it helps to organize the conversation thread.

ADD REPLYlink written 6 months ago by Michael Love22k

Hi Michael,

I just saw this, Thanks a lot for your reply, Here is the link to my new post:

Need help with DESeq2's contrast feature

Thanks
Ashu

 

ADD REPLYlink written 6 months ago by Ashu10
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