HTqPCR problem with replicates
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marco fabbri ▴ 320
@marco-fabbri-1657
Last seen 8.1 years ago
Italy
Hi, I am using TLDA cards with HTqPCR, the cards have 2 samples for each card and the features are in triplicates. I import the card and run limma but I realised that the triplicates are kept apart. As you can see from the last three lines 18S is presented three times but I would like to have a average of the three replicates. qPCRraw= readCtData(files=c("palte_res.txt"), path = NULL, n.features = 384, flag = 4, feature = 6, type = 7, position = 3, Ct = 8, header = TRUE, SDS = TRUE, na.value = 40,n.data=2) ###set the layout (192 for each card) sample2a.order <- factor(rep(c("x","Y"), each=192)) qPCRnew <- changeCtLayout(qPCRraw[,], sample.order = sample2a.order) ###change the name sampleNames(qPCRnew) <- c("Ctrl_R1","Diuron50_R1","Ctrl_R2","Diuron50_R2") #set the group groups = factor(c("Ctrl","Diuron50","Ctrl","Diuron50")) q2.cat=setCategory(qPCRnew, Ct.max = 35,groups = samples,n.category=1) q2.cat=filterCtData(qPCRnew,remove.category="Undetermined" ,n.category=1) #normalized q2.NORM= normalizeCtData( q2.cat,norm="deltaCt",deltaCt.genes=c("ABL1-Hs01104728_m1","MRPL19-Hs0 1040217_m1","HPRT1-Hs03929098_m1")) ######limma design <- model.matrix(~0 + groups) colnames(design) <- c("Ctrl","Diuron50") print(design) contrasts <- makeContrasts(Ctrl-Diuron50, levels = design) qDE.limma <- limmaCtData(q2.NORM, design = design, contrasts = contrasts) qDE.limma $`Ctrl - Diuron50` genes feature.pos t.test p.value adj.p.value ddCt FC meanTarget meanCalibrator 10 18S-Hs99999901_s1 <na> 13.020948738 0.0006195627 0.04484078 2.856187444 0.13810262 -12.10495367 -14.961141111 11 18S-Hs99999901_s1 <na> 11.461949841 0.0009341829 0.04484078 2.958459694 0.12865151 -12.17514617 -15.133605861 12 18S-Hs99999901_s1 <na> 11.851588812 0.0008389948 0.04484078 2.681318944 0.15589873 -12.30213467 -14.98345361
ddCt HTqPCR ddCt HTqPCR • 1.5k views
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Heidi Dvinge ★ 2.0k
@heidi-dvinge-2195
Last seen 10.2 years ago
Hi Marco, > Hi, > > I am using TLDA cards with HTqPCR, the cards have 2 samples for each > card and the features are in triplicates. I import the card and run > limma but I realised that the triplicates are kept apart. As you can > see from the last three lines 18S is presented three times but I would > like to have a average of the three replicates. > In order to use the triplicates you ahve to let limmaCtData() know where the replicates are. In your case, this would mean setting ndups=3, and e.g. spacing=1 if the replicates genes are in consecutive order, or spacing=64 is they're spaced evenly across the 192 wells. The last example in limmaCtData shows an example of how to reorder the rows, and use ndups=2. If this doesn't solve your problem, then please let us know what sort of error or output from limmaCtData you get. HTH \Heidi > qPCRraw= readCtData(files=c("palte_res.txt"), path = NULL, n.features > = 384, flag = 4, feature = 6, type = 7, position = 3, Ct = 8, header = > TRUE, SDS = TRUE, na.value = 40,n.data=2) > > ###set the layout (192 for each card) > sample2a.order <- factor(rep(c("x","Y"), each=192)) > qPCRnew <- changeCtLayout(qPCRraw[,], sample.order = sample2a.order) > ###change the name > sampleNames(qPCRnew) <- c("Ctrl_R1","Diuron50_R1","Ctrl_R2","Diuron50_R2") > #set the group > groups = factor(c("Ctrl","Diuron50","Ctrl","Diuron50")) > > q2.cat=setCategory(qPCRnew, Ct.max = 35,groups = samples,n.category=1) > q2.cat=filterCtData(qPCRnew,remove.category="Undetermined" ,n.category=1) > #normalized > q2.NORM= normalizeCtData( > q2.cat,norm="deltaCt",deltaCt.genes=c("ABL1-Hs01104728_m1","MRPL19-H s01040217_m1","HPRT1-Hs03929098_m1")) > > ######limma > > design <- model.matrix(~0 + groups) > colnames(design) <- c("Ctrl","Diuron50") > print(design) > > contrasts <- makeContrasts(Ctrl-Diuron50, levels = design) > > qDE.limma <- limmaCtData(q2.NORM, design = design, contrasts = contrasts) > > qDE.limma > $`Ctrl - Diuron50` > genes feature.pos t.test > p.value adj.p.value ddCt FC meanTarget > meanCalibrator > 10 18S-Hs99999901_s1 <na> 13.020948738 > 0.0006195627 0.04484078 2.856187444 0.13810262 -12.10495367 > -14.961141111 > 11 18S-Hs99999901_s1 <na> 11.461949841 > 0.0009341829 0.04484078 2.958459694 0.12865151 -12.17514617 > -15.133605861 > 12 18S-Hs99999901_s1 <na> 11.851588812 > 0.0008389948 0.04484078 2.681318944 0.15589873 -12.30213467 > -14.98345361 > > _______________________________________________ > Bioconductor mailing list > Bioconductor at r-project.org > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: > http://news.gmane.org/gmane.science.biology.informatics.conductor >
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