Unexpected Results from Limma background subtraction & marray normalizatoin
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Last seen 6.5 years ago
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]]
Microarray Normalization limma marray Microarray Normalization limma marray • 656 views
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