Random Variance T-Test In R?

Question

[Jordan]

Hi,

I'm doing Microarray analysis and I would like to perform a random variance t-test instead of normal t-test to obtain the p-value. Do we have any packages which are available in R which does this? I could not find them. Any help would be great!

Random variance t-test are available in BRB Tools and I would like to replicate those results using R. Here is the paper which talks about the uses of Random variance t-test.

Thanks!

[int11ap1]

Well, I don't know if it is useful for you, but I use the package limma that does a moderated t-test, taking into account standard variations across the sample in order to overcome limited replication.

[Devon Ryan]

Just to add to this, limma also does information sharing between genes/probes/whatever for variance calculation. Having not gone through the paper thoroughly, though, I can't say how similar its method is to that used by limma.

[Jordan]

I use limma too. But the t-test in the package lets me choose either variance which is equal or unequal, not random. I was looking for a package which can do that for me. I know BRBtools does it. So I wanted to know if there is an equivalent in R.

[Gordon Smyth]

I think you might have misinterpreted the BRB Tools variance model. The random variance model that BRBtools uses is between genes, not between samples, and it is closely analogous to what limma does. Both tools allow variances to be different between genes but the same for samples within each gene. BRB Tools doesn't give any extra flexibility not available in limma.

Answer 1

[Gordon Smyth]

The random variance model of BRB Tools is essentially the same idea as the empirical Bayes model of limma. BRB Tools calls it a random model whereas limma calls it a prior distribution, but mathematically they are the same. limma would be a logical R equivalent of BRB Tools, although limma estimates hyperparameters differently and limma implements additional theory leading to exact small sample tests.