[BioC] spike control normalization
Gordon Smyth
smyth at wehi.edu.au
Wed Jun 29 07:32:30 CEST 2005
limma allows you to normalize on any set of control spots using any of the
normalization methods "loess", "printtiploess", "robustspline". See page 15
of the User's Guide. (Although I don't actually recommend this with
spike-in controls, because of the risk of systematic bias in spike-in
volumes relative to sample volumes.)
The technique is simply to set up a vector or matrix 'w' which is 1 for
controls that you want to use for normalization and 0 otherwise. For example,
MA <- normalizeWithinArrays(RG, method="loess", weights=w)
will put a loess curve through the control spots and will subtract this
curve from all the other spots.
You have asked to subtract the mean log-ratio for the spike-in from the
other spots. This is not specifically provided for in limma (I don't
recommend it), but it is easy. Suppose 'isSpikeIn' is a vector of
TRUE/FALSE indicating which probes are spike-in controls. Then
MA <- normalizeWithinArrays(RG, method="none")
m <- colMeans(MA$M[isSpikeIn,],na.rm=TRUE)
MA$M <- MA$M - ( matrix(1,nrow(MA),1) %*% m )
Gordon
>[BioC] spike control normalization
>NATALIA F TCHETCHERINA nxt7 at psu.edu
>Tue Jun 28 19:30:49 CEST 2005
>
>Hello all,
>I have experiment where a large fraction of genes are expected to be
>differentially expressed. That why I would like to normalize the data using
>spike control spots (I really would like to do within arrays normalization
>just
>subtract over the whole array ( or witnin i-th block) mean of log-ratio of
>spike control from log-ratio for each gene). I use Limma.
>My question is: does limma have options for such normalization?
>If it does not that package I should use?
>
>Sincerely, Natalia.
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