[BioC] Question about quantile normalization and NA value

[H at mamba.fhcrc.org]

Dear all,

I have a quation about quantile normalization and NA value.

I'm going to normalize the microarray data by "normalizeBetweenArrays" which is the quantile normalization function in "limma" package.
I normalized a data with NA as follows:

> x <- matrix(c(100,15,200,250,110,16.5,220,275,120,18,240,300),4,3)
> colnames(x) <- paste("Chip",1:3, sep="")
> rownames(x) <- c("RNA-A","RNA-B","RNA-C","RNA-D")
>
> x
      Chip1 Chip2 Chip3
RNA-A   100 110.0   120
RNA-B    15  16.5    18
RNA-C   200 220.0   240
RNA-D   250 275.0   300
>
> normalizeBetweenArrays(x)
      Chip1 Chip2 Chip3
RNA-A 110.0 110.0 110.0
RNA-B  16.5  16.5  16.5
RNA-C 220.0 220.0 220.0
RNA-D 275.0 275.0 275.0
>
> y <- x
> y[2,2] <- NA
>
> normalizeBetweenArrays(y)
          Chip1     Chip2     Chip3
RNA-A 134.44444  47.66667 134.44444
RNA-B  47.66667        NA  47.66667
RNA-C 226.11111 180.27778 226.11111
RNA-D 275.00000 275.00000 275.00000


I asuume the normalized y is a bit far away from normalized y. Does only one NA induce this large effect ?
Should I normalize after replacing NA with some value, such as median(x[2,],na.rm=T) ?
My environment is limma Version 3.16.6, R version 3.0.1.

Thanks

 -- output of sessionInfo(): 

Dear all,

I have a quation about quantile normalization and NA value.

I'm going to normalize the microarray data by "normalizeBetweenArrays" which is the quantile normalization function in "limma" package.
I normalized a data with NA as follows:

> x <- matrix(c(100,15,200,250,110,16.5,220,275,120,18,240,300),4,3)
> colnames(x) <- paste("Chip",1:3, sep="")
> rownames(x) <- c("RNA-A","RNA-B","RNA-C","RNA-D")
>
> x
      Chip1 Chip2 Chip3
RNA-A   100 110.0   120
RNA-B    15  16.5    18
RNA-C   200 220.0   240
RNA-D   250 275.0   300
>
> normalizeBetweenArrays(x)
      Chip1 Chip2 Chip3
RNA-A 110.0 110.0 110.0
RNA-B  16.5  16.5  16.5
RNA-C 220.0 220.0 220.0
RNA-D 275.0 275.0 275.0
>
> y <- x
> y[2,2] <- NA
>
> normalizeBetweenArrays(y)
          Chip1     Chip2     Chip3
RNA-A 134.44444  47.66667 134.44444
RNA-B  47.66667        NA  47.66667
RNA-C 226.11111 180.27778 226.11111
RNA-D 275.00000 275.00000 275.00000


I asuume the normalized y is a bit far away from normalized y. Does only one NA induce this large effect ?
Should I normalize after replacing NA with some value, such as median(x[2,],na.rm=T) ?
My environment is limma Version 3.16.6, R version 3.0.1.

Thanks

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