Difference between revisions of "ExploreSwirl.R"
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# Abundance apears to be a slight mixture (hump more prevelant with background subtraction) | # Abundance apears to be a slight mixture (hump more prevelant with background subtraction) | ||
| + | # Mixture could be of exponential and low expressing distribution on raw scale | ||
hist(rowMeans(MA$A), breaks=nbreaks) | hist(rowMeans(MA$A), breaks=nbreaks) | ||
| − | # Abundance, observed exponential decay on raw scale | + | # Abundance, observed exponential like decay on raw scale |
hist(2^rowMeans(MA$A), breaks=nbreaks) | hist(2^rowMeans(MA$A), breaks=nbreaks) | ||
qqplot(rexp(10000,1/6000), 2^rowMeans(MA$A)) | qqplot(rexp(10000,1/6000), 2^rowMeans(MA$A)) | ||
abline(0,1) | abline(0,1) | ||
Revision as of 23:17, 29 August 2006
library(marray) library(limma)
bc.method <- "subtract" nbreaks <- 100
dataDir <- system.file("swirldata", package = "marray")
RG <- read.maimages(path=dataDir, source="spot", ext="spot")
- Right skew
plotDensities(RG, log=FALSE)
MA <- MA.RG(RG)
- [[[[1]]]] not centred
hist(rowMeans(MA$M), breaks=nbreaks) hist(rowMeans(MA$A), breaks=nbreaks) for(i in seq(ncol(RG))) {
plotMA(RG, array=i)
}
MA <- normalizeWithinArrays(RG, method="loess", bc.method = bc.method)
for(i in seq(ncol(RG))) {
plotMA(MA, array=i) Sys.sleep(0.5)
}
- CLT: After normalization the distribution is centred around 0 (right long tail)
hist(rowMeans(MA$M), breaks=nbreaks) hist(2^rowMeans(MA$M), breaks=nbreaks)
- Abundance apears to be a slight mixture (hump more prevelant with background subtraction)
- Mixture could be of exponential and low expressing distribution on raw scale
hist(rowMeans(MA$A), breaks=nbreaks)
- Abundance, observed exponential like decay on raw scale
hist(2^rowMeans(MA$A), breaks=nbreaks) qqplot(rexp(10000,1/6000), 2^rowMeans(MA$A)) abline(0,1)
