Question: Obtaining clean data after adjusting for batch effects using SVA
gravatar for Momeneh Foroutan
2.8 years ago by
Momeneh Foroutan 10 wrote:

Hi all (and Andrew Jaffe),

I know there is a post related to this topic here "Back-estimating batch variables from SVA for ComBat?" but I actually have a question about the answer given by Andrew to that post.

Andrew has kindly suggested using the below function to obtain the clean data adjusted for surrogate variables:

cleaningY = function(y, mod, svaobj) {
# and implement it like this: 
mod = model.matrix(~[whatever your model is]) # specify the model 
svaobj = sva(y, mod) # y is your expression matrix 
cleany = cleaningY(y,mod,svaobj)

So my question is about the sva() function in the above example. why did not he give mod0 and to sva() for generating svaobj? it makes a huge difference in case of my data set. the function estimated two surrogate variables for my data, and I suppose that I should run sva() in this way:

svobj = sva(m, mod, mod0, =   ## m is the expression matrix

While if I run sva() without assigning mod0 and, it gives me 77 surrogate variables! Isn't that we must give it mod0 because we need a null model to compare to the model matrix being used to fit the data?

Thanks in advance for any explanation.



ADD COMMENTlink written 2.8 years ago by Momeneh Foroutan 10


I have the exact same question. Any updates on this?


ADD REPLYlink written 9 months ago by wamiqsaifi0
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