edgeR: Nested interactions model matrix MISSING COEFFICIENTS
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xluong • 0
@xluong-11510
Last seen 8.4 years ago

Hello,

I am trying to perform DE gene analysis on RNA-Seq data. My groups consist of animals from two different populations (SD v. XE) and two different treatments (CON v. E2). I'm trying to look at nested interactions and am following section 3.3.2 in the edgeR user guide.

My metadata 'meta' is as follows:

samples treat pop group 1 THXL1A E2 SD E2.SD 2 THXL1B CON SD CON.SD 3 THXL1C CON XE CON.XE 4 THXL1D E2 XE E2.XE 5 THXL1E CON SD CON.SD 6 THXL1F E2 SD E2.SD 7 THXL7 CON XE CON.XE 8 THXL8 E2 XE E2.XE 9 THXL9 CON SD CON.SD 10 THXL10 CON SD CON.SD 11 THXL11 E2 SD E2.SD 12 THXL12 E2 SD E2.SD

My script looks like this:

meta$treat <- relevel(meta$treat, ref="CON") #sets reference level as 'CON'
design <- model.matrix(~treat + treat:pop, data=meta)                                                                                                                   
dispData <- estimateDisp(dgeData, design, robust=TRUE)
fit <- glmFit(dispData, design)

However, when I look at  'design,' I only get 4 coefficients (missing "treatCON:popSD" and "treatE2:popSD"):

[1] "(Intercept)"    "treatE2"        "treatCON:popXE" "treatE2:popXE"

As opposed to the 6 coefficients they list in the user guide.

Please help!

limma edger nested design • 1.2k views
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Entering edit mode
@ryan-c-thompson-5618
Last seen 4 months ago
Icahn School of Medicine at Mount Sinai…

With 2 populations and 2 treatments, there are 4 possible combinations of population and treatment. Hence, you have 4 coefficients. If you're not sure how to interpret these 4 coefficients, consider the advice given in the very first sentence of the section of the user's guide that you cited: "We generally recommend the approach of the previous section [3.3.1], because it is so explicit and easy to understand."

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