Fourteen days since my last post. Quite a while, indeed. Mostly I've been stumbled with work and some health related issues. Anyway, I thought I'd follow up on the meta analysis matter I discussed in my last post.

It turns out that it's a fault of both limma and the data sets, because apparently the raw data found in the Stanford Microarray Database have different length, gene-wise (a result of not all spots on the array being good?) and limma itself does need equal length tables to form a single object (I stumbled upon the same problem when doing my thesis, but I used a hack to work around it), and does not perform any checking.

According to the documentation, the "merge" command should be used to deal with these cases, but here's what I get:

{{< highlight R >}}

RG1 = read.maimages(file="file1.txt",source="smd") Read file1.txt RG2 = read.maimages(file="file2.txt",source="smd") Read file2.txt merge(RG1,RG2) Error in merge(RG1,RG2): Need row names to align on rownames(RG1) NULL rownames(RG2) NULL {{< / highlight >}}

I'm going to ask the Bioconductor ML and see what they tell me.