Meaning of multiple coef in topTable, limma.
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@zhangjianhai-12955
Last seen 4.3 years ago

Dear Sir or Madam,

I am interested in understanding the meaning of "multiple coef" in topTable(), limma package.

For instance, I understand "topTable(fit,coef=1)", but what does "topTable(fit,coef=1:5) mean"? 

Thanks in advance.

Regards,

Jianhai

toptable coef • 3.2k views
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svlachavas ▴ 830
@svlachavas-7225
Last seen 6 months ago
Germany/Heidelberg/German Cancer Resear…

Dear Zhang,

when you define multiple coefficients (or no coefficients set), you actually perform an ANOVA-like comparison (similarly if you instead use topTableF), where your null hypothesis would be that there are no DE between any of the conditions/defined coefficients. Thus, in the first case when you define a specific coefficient, you test and set your null hypothesis regarding only this specific contrast. For a more detailed example, you can check the following post:

Model matrix for anova in limma

Best,

Efstathios

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@zhangjianhai-12955
Last seen 4.3 years ago

Dear Efstathios,

Thanks for your explanation very much. I have a similar question in edgeR. 

For example, I have the following design matrix, and I want to compare each patient to the other 2 patients: 8vs33, 8vs51, 33vs51.

Can you tell me how to set the coeff in "lrt <- glmLRT(fit, coef=)", "topTags(lrt)" in a simple way? So that I don't need to set the pairwise coef/contract one by one. Thanks in advance.

In my research I have 70 samples and need to compare each to the rest 69 samples, here I just use 3 samples as a toy example for simplicity purpose.

I know I can set the pairwise contract in such a way: contrast=c(0,0, ,,,,,,,,,-1,1,0,0,0,0,,,,,,0,000), but considering so many samples, it is not convenient to set the pairwise contracts one by one. So is there a one-step way to compare all pairs simultaneously?

Design matrix:

    Patient8 Patient33 Patient51 

8N          1            0            0       

8T          1            0            0       

33N        0            1           0       

33T        0            1           0       

51N        0            0           1       

51T        0            0           1       

 

Regards,

Jianhai

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For the benefit of future readers, this follow-up question was re-posted and answered here: edgeR multiple coeff in "lrt <- glmLRT(fit, coef=)"

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