I did not understant one thing. I found some posts regarding this question but I couldn't find an answer for my question.
If I have 4 groups, each one with 3 replicates: 1,1,1,2,2,2,3,3,3,4,4,4, and I want to compare all of them against each other, how can I do that?
x <- read.delim("table.csv",row.names="genes") group <- factor(c(1,1,1,2,2,2)) y <- DGEList(counts=x,group=group) y <- calcNormFactors(y) design <- model.matrix(~group) y <- estimateDisp(y,design) et <- exactTest(y)
In this case, I am comparing groups 1 and 2. Them I would do that for the other comparisons (like
group <- factor(c(3,3,3,4,4,4))). Can I do that this way?
Or, instead of that should I do something like this?:
x <- read.delim("table.csv",row.names="genes") group <- factor(c(1,1,1,2,2,2,3,3,3,4,4,4)) y <- DGEList(counts=x,group=group) y <- calcNormFactors(y) design <- model.matrix(~group) y <- estimateDisp(y,design) fit <- glmQLFit(y,design) qlf_quasi <- glmQLFTest(fit,coef=2:4) topTags(qlf_quasi)
The problem is that I don't know exactly how to use
coef for this kind of comparisons.
coef=2:4 will compare all groups against the control group, but I do not have a control group, I want to compare everything (or in other cases I want to choose specific comparisons. How can I choose exactly the comparisons I like to do?
Other problem is that when I use a code like this the output is a single table with multiple comparisons, but just one p-value and one FDR. I need separeted p-values for each comparison (like in the pos-tests for ANOVA or something like this).
It would be great if you can help me.