When should you use SVA vs. ComBat?

Question

[chengzhao41]

Hi,

I'm looking for some advice and tips on when to use SVA vs. ComBat for homogenizing microarray gene expression data.

Thanks,
Cheng

Answer 1

[Devon Ryan]

N.B., I'm being a bit loose with terminology below, but that should still suffice.

Combat is used when you know how the batch effect is structured. For example, you have microarrays prepared and run at different dates, where you expect "date" to cause a change in and of itself. SVA is used when you suspect that your data has underlying variation that's not being caused by the biology you're interested in or factors that you can easily identify. This often happens when there are a combination of background effects affecting your data, but you don't know about them and aren't remotely interested in studying them.

[brentp]

In short: If you know a covariate that drives the batch effect, use ComBat. If you don't, use SVA.

[susanna.downing]

Are there better methods for removing batch effect in R than ComBat, or is that still a preferred method?
I seem to be having some "batch effect" but it relates more to sample prep as all were run on the same chip, but I want to be sure I'm analyzing correctly.

Answer 2

[kangyueapril]

They are same thing. In sva package, the combat method is contained. You can use combat in sva package. Beside, there are some other useful function in sva about adjust batch bias.