Combine multiple groups on comparison by edgeR
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7 months ago
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I'm trying to compare multiple conditions on edgeR. I have looked up into previous posts and read through edgeR's user guide, yet still don't have a clear answer.

My question is whether we can combine subgroups as one group by design matrix on comparison.

For example, if I have 4 groups to compare, after normalization as below,

d <- DGEList(counts=count, lib.size=size, group=group)
d <- calcNormFactors(d, method="RLE")
d <- estimateDisp(d)
design <- model.matrix(~0+group, data=d$samples) colnames(design) <- levels(d$samples\$group)
fit <- glmQLFit(d, design)


I understand that if we want to compare group 2 vs group 1, the pipeline would be

group2vs1 <- makeContrasts(group2-group1, levels=design)
qlf.2vs1 <- glmQLFTest(fit, contrast=group2vs1)


In this case,

coef = (-1, 1, 0, 0)


How about if I want to compare group 1 vs the rest? Does the codes below do what is desired?

group1vsrest <- makeContrasts(group1-(group2+group3+group4)/3, levels=design)


which gives

coef = (-1, 0.333, 0.333, 0.333)


Or should I do without multiple by 1/3

group1vsrest <- makeContrasts(group1-(group2+group3+group4), levels=design)


which corresponds to

coef = (-1, 1, 1, 1)


I've read some lines on edgeR's user guide mentioning the former would compare group1 and the mean of group 2-4. Does the "mean" mean that we treat group2-4 as one group? Do I need to make another design variable attributing group1 and the rest separately into two categories to do this comparison?

glm rna-seq edgeR • 309 views