I saw this post from a while ago regarding a similar issue: edgeR: Problem with subsetting a DGEList in latest package version

>d$samples[1:6,]

sample                                                   lib.size    norm.factor  type    time

preExercise_TAGGCTGACTTGAG.1      856    1.1020236     B  pre
preExercise_TCCATCCTCGTTAG.1     1033    1.2198739     B  pre
pbmc001_TTGAGGACTTTCAC.1          703    1.2050717     B  pre
pbmc001_AGTCGCCTGCTTAG.1         1230    1.0304974     B  post
pbmc001_TACTACACAGCACT.1         1053    0.9790636     C  post
pbmc001_TAAACAACCCTTAT.1          895    1.1032946     D  pre

...

I am trying to do differential expression of things only of type 'B', with the time frame as the group 'post vs pre'. I though the easiest way would be to just subset d via:

d.B = d[,grep('B',d$samples$type)]

But I get the error:

Error in `$<-.data.frame`(`*tmp*`, "group", value = integer(0)) : 
  replacement has 0 rows, data has 226

Is there a proper way of doing differential expression on just a subset of the DGEList? 

I got around this by employing the method from the post Iinked:

B=grep('B',d$samples$type)
test=DGEList(d$counts)
test=test[,B]

Then replacing test$samples with its proper subset from d:

test$samples=d$samples[Bcells,]

This just seems sort of hacky...

Now that you've verified you're running the latest version of edgeR, I've looked a bit more closely at your example and error.

It seems that you have somehow constructed a DGEList (d) with a $samples data.frame that doesn't have a group column -- what were the commands you used to construct d?

In any event, try adding a group column, like so:

d$samples <- transform(y$samples, group=paste(type, time, sep="_"))

Then try subsetting by columns again ...

Also, adding such a group column can be useful in  your downstream analysis since you can now analyze your experiment as a one-way layout:

design <- model.matrix(~ 0 + group, d$samples)

You can then construct contrasts with makeContrasts that are easy-to-interpret arithmetic over the columns of design.

A DGEList object needs to satisfy some minimum conditions to be a valid object. If you change a DGEList object so that it no longer satisfies these minimum conditions, then operations such as subsetting can no longer be guaranteed to work.

help("DGEList-class") explains what a DGEList object is assumed to contain. It explains that 'group', 'lib.size' and 'norm.factors' are compulsory columns for the d$samples data.frame, so you cannot remove them.