[BioC] high poportion of identical expression measure with RMA and 3
arrays
Adaikalavan Ramasamy
ramasamy at cancer.org.uk
Mon Sep 13 19:12:42 CEST 2004
I was pondering about the issue of minimum number of required arrays for
RMA and GCRMA when I came across a thread by James MacDonald
http://files.protsuggest.org/biocond/html/3347.html. He mentioned that
median polish has a peculiar feature that returned identical values for
odd number of arrays, especially 3 arrays. I am not sure if this issue
has been addressed since but here is some empirical evidence to support
this in case anyone is interested.
### Codes ###
library(affy)
v <- rep(NA, 10)
for(i in 2:10){
a <- exprs( justRMA( filenames=list.celfiles()[1:i] ))
v[i] <- mean( apply(a, 1, var) == 0 ) # proportion identical
gc(); print(i)
}
100*v
### Results ###
# Dataset 1 : hu6800 (west)
> 100 * v
[1] NA 0.0000000 13.1434984 0.0000000 0.1262449 0.0000000
[7] 0.0000000 0.0000000 0.0000000 0.0000000
# Dataset 2 : hgu-95av2 (febbo)
> 100 * v
[1] NA 0.007920792 7.912871287 0.000000000 0.095049505 0.000000000
[7] 0.000000000 0.000000000 0.000000000 0.000000000
# Dataset 3 : HGU-133A (pga)
> 100 * v
[1] NA 1.5348023 16.0750348 0.0000000 0.3590181 0.0000000
[7] 0.0000000 0.0000000 0.0000000 0.0000000
When there are 3 arrays, there is a high proportion of probesets with
identical values (i.e. zero variance). I am trying to see if the same
effect can be seen with justGCRMA.
misc : affy 1.4.32, gcrma 1.1.0, R-1.9.0 (12/04/2004) and FC 2.
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