limma with interaction term
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Jitendra ▴ 10
@nabiyogesh-11718
Last seen 56 minutes ago
United Kingdom

I want to run some epigenome wide association studies based on city and pollutant type, could you please suggest if I can get DNA methylation sites (CpG) association based on pollutant type for each city. like below I am trying to find Pb toxic elements association site in four different cities which has varying level of Pb. we do have 10 toxic element so not sure should I run model with one toxic element at a time or should include all in this model?

#model matrix

var<-model.matrix(~log2Pb*City + sex + Age +CD8T +CD4T +NK + Bcell +Mono, data=data1)

fit<-lmFit(mval,var)


fit2<-eBayes(fit,trend=TRUE, robust=TRUE)

probe<-topTable(fit2,adjust="BH",coef=???,num=Inf)

try to run interaction model using limma but not sure if this is the right approach and what to mention in coef????

Thanks for your all help!

R biostatistics limma Epigenetics • 222 views
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@james-w-macdonald-5106
Last seen 2 days ago
United States

The interaction term should be the last one in your design matrix, so

topTable(fit2, ncol(var), Inf, p.value = 0.05)

Will give you the CpGs with an FDR<0.05 for the interaction term.

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Jim, there are 4 cities so the interaction will be 3 coefficients.

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Indeed. Thanks for pointing that out!

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@gordon-smyth
Last seen 2 hours ago
WEHI, Melbourne, Australia

There are many ways to specify the interaction coefficients, but maybe the easiest here would be:

topTable(fit2, coef=grep(":",colnames(var)), num=Inf)

To see how this works, just type colnames(var) or colnames(fit2). You will easily see the interaction coefficients. Then you specify them to topTable either by name or by number.

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