Hello everyone,

I am trying to use Limma for microarray background subtraction and marray
for normalization.
To do this, I need to transfer my data between RGlist (for limma) and
marray objects.
I think that using limma for background subtraction and marray for
normalization is standard, so hopefully someone on here has experience
converting between the two.

I think I'm doing this correctly, but the normalized data I am getting back
is very different from normalization on the same data I had previously done
in SMD: the red/green ratios are all very close to 0 (SD < 0.5 per array).
I know that my previous data-processing scheme was reasonable, so there
must be something I'm doing wrong with limma/microarray.

I realize this is a very broad question, but does anyone* *see* any glaring
mistakes that could be corrupting my data and leading to invalid normalized
red/green ratios?*

In particular, since I've already done background subtraction before
supplying the data to marray, *should I be setting maRb and maGb to 0'*s?
(not doing this introduced a lot of NAs.)

This is my simplified code:

      RGraw <- read.maimages(file,"genepix",wt.fun=wtflags(0.1),
verbose=FALSE)
      # RGraw: raw red and green fluorescence values from .gpr files

      RGsubbed<-backgroundCorrect(RGraw, method = "edwards", verbose =
FALSE)
      # RGsubbed : background-subtracted red and green fluorescence values

      rawmarray <-read.GenePix(file)
      # retreive all original .gpr data

      rawmarray@maRf<-RGsubbed$R
      rawmarray@maGf<-RGsubbed$G
      #splice in background-subtracted red and green values from limma to
marray

      rawmarray@maGb<-matrix(data = 0, nrow = nrow(rawmarray@maGb), ncol =
ncol(rawmarray@maGb))
      rawmarray@maRb<-matrix(data = 0, nrow = nrow(rawmarray@maRb), ncol =
ncol(rawmarray@maRb))
      #set background values in marray to 0, since I have already performed
background subtraction in Limma

      normMarray<-maNorm(rawmarray, NormMethodNames[n])
      #perform normalization using marray

      ratios<-maM(normalized)
      #retrieve normalized red/green ratios

      stdev<-sd(na.omit(ratios))
      #these standard deviations are always way lower than what I got in
SMD, regardless of background subtraction/normalization method


Thanks very much for any help you can offer... I've been banging my head
against the wall and crawling through browser() for days trying to figure
this out....

-- 
Ellen Sebastian
B.S. Candidate, Biomedical Computation
Stanford University, Class of 2015

	[[alternative HTML version deleted]]

