[BioC] A question on scaling normalization proposed by Mark Robinson Group

[Mark Robinson]

Hi Sunghee.

First, the standard use of calcNormFactors() is described in the user guide in the "Normalization" section.  Briefly it goes something like this ...

[...]
f <- calcNormFactors(D)  # D is table of counts
d <- DGEList(counts = D, group = g, lib.size = colSums(D) * f)
[...]

You seem to be modifying the raw data, which is outside the standard use case (but could be useful depending on what you are doing).  However, if you are doing a differential expression analysis downstream of this (e.g. edgeR), we wouldn't recommend modifying the raw data.

But, if you really want to have normalized data in this way, you should divide by the library sizes that edgeR would use.  Note also that your code, as written, will not work right correctly multiplying the factors in.  Consider doing something like:

fM <- outer( rep(1,nrow(D)), colSums(D)*f )  # create matrix of same dimension
normD <- D / fM

Hope that helps.

Cheers,
Mark

On 2010-07-29, at 1:08 PM, sunghee OH wrote:

> Hi Guys,
> 
> 
> I am trying to run scaling normalization in egder package using
> calcNormFactors.
> Btw, this function returns only a scaling factor values for each sample.
> so, a quick question: after i obtain such scaling factors from the function,
> i need to simply and manually compute as like below further?
> 
> norm_data <- data_mat * scaling factors / library size
> 
> 
> this procedure is the very scaling normalization proposed by Robinson.
> 
> 
> is that correct? if there is anyone who knows that, plz throw an reply.
> Thanks --S
> 
> 	[[alternative HTML version deleted]]
> 
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------------------------------
Mark Robinson, PhD (Melb)
Epigenetics Laboratory, Garvan
Bioinformatics Division, WEHI
e: m.robinson at garvan.org.au
e: mrobinson at wehi.edu.au
p: +61 (0)3 9345 2628
f: +61 (0)3 9347 0852
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