[BioC] HTqPCR problems

Simon Melov smelov at buckinstitute.org
Tue Jun 26 21:01:16 CEST 2012


Hi,
I'm having some troubles selectively sub-setting, and graphing up QPCR data within HTqPCR for Biomark plates (both 48.48 and 96.96 plates). I'd like to be able to visualize specific genes, with specific groups we run routinely on our Biomark system. Typical runs are across multiple plates, and have multiple biological replicates, and usually 2 or more technical replicates (although we are moving away from technical reps, as the CVs are so tight).

Can anyone help with this? Heidi?

raw6=readCtData(files="Chip6.csv", format="BioMark", n.features=48, n.data=48, samples=samples)
#Ive read the samples in from a separate file, as when you read it in, it doesnt take the sample names supplied in the biomark output#
#Next, I want to plot genes of interest, with samples of interest, and I'm having trouble getting an appropriate output#

g=featureNames(raw6)[1:2]
plotCtOverview(raw6, genes=g, groups=groupID$Treatment, col=rainbow(5))

#This plots 1 gene across all 48 samples#
#but the legend doesnt behave, its placed on top of the plot, and I cant get it to display in a non-overlapping fashion#
#I've tried all sorts of things in par, but nothing seems to shift the legend's position#

#I now want to plot a subset of the samples for specific genes#
> LOY=subset(groupID,groupID$Treatment=="LO" | groupID$Treatment== "LFY")
> LOY
   Sample Treatment
2     L20       LFY
5     L30       LFY
7     L45        LO
20    L40        LO
27    L43        LO
33    L29       LFY
36    L38        LO
40    L39        LO
43    L23       LFY


> plotCtOverview(raw6, genes=g, groups=LOY, col=rainbow(5))
Warning messages:
1: In split.default(t(x), sample.split) :
  data length is not a multiple of split variable
2: In qt(p, df, lower.tail, log.p) : NaNs produced
> 

#it displays the two groups defined by treatment, but doesnt do so nicely, very skinny bars, and the legend doesnt reflect what its displaying#
#again, I've tried monkeying around with par, but not sure what HTqPCR is calling to make the plots#

please help!

thanks

Simon.



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