Dear Community,

i would like to address an "issue" i have discovered while importing and pre-processing an agilent microarray dataset  in R. More specifically, part of my code is the following:

...
SDRF <- read.delim("GSE12435.sdrf.txt",check.names=FALSE,stringsAsFactors=FALSE)
files <- list.files(pattern = "GSM")
dat <- read.maimages(files, source="agilent", green.only=T)

y <- backgroundCorrect(dat,method="normexp")
y <- normalizeBetweenArrays(y,method="quantile")

But then, when inspecting the range of the values of my normalized dataset, i noticed something strange:

> range(y$E)
[1] -1.54555 18.77689

> mat <- y$E
> length(mat[mat<0])
[1] 39
> mat[mat<0]
 [1] -0.797841119 -1.545549855 -0.138353557 -0.797841119 -0.797841119 -0.797841119 -1.123788523
 [8] -0.138353557 -1.123788523 -1.545549855 -0.138353557 -0.797841119 -0.138353557 -1.545549855
....(the rest of the negative values)

Thus, how should i deal with these negative values ? it has something to do with the background correction ? Maybe a naive solution is to add an offset, but of which value ? In other words, is a "general" approach on the offset, in not to change it in various other datasets with similar negative values" ?  I also share a histogram of my normalized expression values:

https://www.dropbox.com/s/hokwmhh1ib2jo8n/histogram.png?dl=0

Any help would be great !!

Konstantinos

There isn't an issue here. Those are log transformed values, and any normalized value that is < 1 will end up being negative after taking logs.