Hi Franklin, Replies below, On 28 February 2013 20:36, Franklin Johnson [guest] <guest@bioconductor.org>wrote: > > Dear Maintainer, > > I have created my.qPCRBatch object read into R using the ReadqPCR package: > > rownames(exprs(qPCRBatch)) > [1] "actin_14d_TechReps.1" "actin_14d_TechReps.2" "actin_1d_TechReps.1" > "actin_1d_TechReps.2" "actin_3d_TechReps.1" "actin_3d_TechReps.2" > [7] "actin_7d_TechReps.1" "actin_7d_TechReps.2" "lox22_14d_TechReps.1" > "lox22_14d_TechReps.2" "lox22_1d_TechReps.1" "lox22_1d_TechReps.2" > [13] "lox22_3d_TechReps.1" "lox22_3d_TechReps.2" "lox22_7d_TechReps.1" > "lox22_7d_TechReps.2" > > combinedTechReps=combineTechReps(qPCRBatch) > > combinedTechReps > qPCRBatch (storageMode: lockedEnvironment) > assayData: 8 features, 2 samples > element names: exprs > protocolData: none > phenoData > sampleNames: MeJa Triton.X > varLabels: sample > varMetadata: labelDescription > featureData: none > experimentData: use 'experimentData(object)' > Annotation: > > I have also generated the deltaCq values using: > > hkgs="actin_1d" > > qPCRBatch.norm=deltaCq(combinedTechReps, hkgs=hkgs, calc="arith") > > head(exprs(qPCRBatch.norm)) > MeJa Triton.X > actin_14d 0.655 0.260 > actin_1d 0.000 0.000 > actin_3d -0.120 0.095 > actin_7d 0.465 0.145 > lox22_14d 2.755 3.530 > lox22_1d 0.735 2.740 > > Now, to advance to Section 5.3, do I need to use qPCRBatch.norm. Or, did R > populate qPCRBatch object with this deltaCq data? In other words, for > Section 5.3, does the deltaDeltaCq function calculate deltaDeltaCq using > deltaCq obtained in 5.1, or does it calculate deltaDeltaCq from the raw Cq > data? > >From the raw data > > However, I get error message when advancing from Section 5.1 to 5.3 using > qPCRBatch.norm: > > contM<-cbind(c(0,0,0,0,1,1,1,1), c(1,1,1,1,0,0,0,0)) > > colnames(contM)=c("MeJa", "Triton.X") > > rownames(contM)=rownames(exprs(qPCRBatch.norm)) > > contM > MeJa Triton.X > actin_14d 0 1 > actin_1d 0 1 > actin_3d 0 1 > actin_7d 0 1 > lox22_14d 1 0 > lox22_1d 1 0 > lox22_3d 1 0 > lox22_7d 1 0 > > hkgs<-"actin_1d" > > ddCq.norm=deltaDeltaCq(qPCRBatch.norm, maxNACase=0, maxNAControl=0, > hkgs=hkgs, contrastM=contM, case="MeJa", control="Triton.X", > statCalc="geom") > Error in .local(qPCRBatch, ...) : subscript out of bounds > > I tried many attempts to alter the subscripts to no success. So, I > attempted to use the vignette to see how to work with the data. However, I > got the same result: > > head(exprs(qPCRBatch.norm)) > fp1.day3.v fp2.day3.v fp5.day3.mia fp6.day3.mia > fp.3.day.3.v fp.4.day.3.v fp.7.day.3.mia fp.8.day.3.mia > Actb.Rn00667869_m1 0.000000 0.000000 0.000000 0.000000 > 0.000000 0.000000 0.000000 0.000000 > Adipoq.Rn00595250_m1 0.016052 -0.116520 2.933523 2.540987 > -0.178971 -0.563263 2.458509 2.736475 > Adrbk1.Rn00562822_m1 NA NA 6.566628 6.642561 > NA NA 3.737100 6.873568 > Agtrl1.Rn00580252_s1 4.899380 5.035841 6.397364 5.680837 > 5.220796 4.425364 4.794776 5.345202 > Alpl.Rn00564931_m1 12.531942 11.808657 13.035166 12.239549 > 12.394802 11.772896 12.110000 12.255186 > B2m.Rn00560865_m1 0.741558 0.890717 2.040470 2.234605 > 0.505516 0.877598 1.927563 1.903269 > > contM<-cbind(c(0,0,1,1,0,0,1,1), c(1,1,0,0,1,1,0,0)) > > colnames(contM)<-c("interestingPhenotype", "wildTypePhenotype") > > rownames(contM)=sampleNames(qPCRBatch.taqman) > > contM > interestingPhenotype wildTypePhenotype > fp1.day3.v 0 1 > fp2.day3.v 0 1 > fp5.day3.mia 1 0 > fp6.day3.mia 1 0 > fp.3.day.3.v 0 1 > fp.4.day.3.v 0 1 > fp.7.day.3.mia 1 0 > fp.8.day.3.mia 1 0 > > hkg="Actb-Rn00667869_m1" > > ddCq.grr<-deltaDeltaCq(qPCRBatch.norm, hkgs=hkg, contrastM=contM, > case="interestingPhentype", control="wildTypePhenotype", > + statCalc="arith") > Error in .local(qPCRBatch, ...) : subscript out of bounds > > It appears you are trying to run deltaDeltaCq() on already normalised data. The example in the vignette runsdeltaDeltaCq() on raw data: qPCRBatch.norm <- deltaCq(qPCRBatch = qPCRBatch.taqman, h = hkgs, calc="arith") Where did you get the example above where you run deltaDeltaCq() on qPCRBatch.norm? It *shouldn't* be in the vignette, but let me know if you find it somewhere so I can eliminate it. > I also made attempts to change this subscript as well, e.g. hkg<=>hkgs, > removed hkgCalc since only using one hkg, but to no success. > > Also, I see for the qPCR.TechReps.txt.example there is a control gene for > each the case detector, respectively. > Unfortunately, you geNorm and NormFinder with example.taqman. However, for > the qPCRBatch.TechReps.example-type of datafile-, which detector do you > choose to normalize the data? In other words, how do you set up your > contrast matrix to match caseA vs. caseB vs. control? > I assume I could do this with the contrast matrix using cbind(c(caseA), > (caseB), (control)), but would NormqPCR::deltaDeltaCq understand this > language? > No - deltaDeltaCq is only for single contrast e.g. caseA - control or caseB - control. You could perhaps use deltaCq normalisation on everything and then build a more complex model. > > Lastly, how to deal with various timepoints: > I have 3 different biological collections: > 1) 1.5, 2) 2, and 3) 3.5. > Two samples per collection (control, treated), and testing only 12 > individual genes plus actin as control gene in each sample and biological > rep, which data for each gene has 4 (1day, 3day, 7day, and 14day) > timepoints (in both control and treated samples as well as for target and > control genes). > Case Control > actin_14d 0 1 > actin_1d 0 1 > actin_3d 0 1 > actin_7d 0 1 > lox22_14d 1 0 > lox22_1d 1 0 > lox22_3d 1 0 > lox22_7d 1 0 > > Right now, I'm only utilizing one data file(one sample): Biological > collection at 1.5. In this file I have both reference genes and the > respective target genes for each timepoint(as shown above). For > deltaDeltaCq function, do I need a second file to compare 1.5 with (e.g. 2 > and/or 3.5), because I'm currently using the featureNames() and not the > sampleNames()? > So, getting an error? This is not logical since I got same error with the > NormqPCR vignette. > > Again, the deltaDeltaCq method employed here is fairly simple, subtracting the housekeeping gene value(s) from the Cq values and then subtracting control from case (with appropriate 2^ transformations). Cheers, Jim > Any suggestions is greatly appreciated. > Regards, > Franklin > > -- output of sessionInfo(): > > > sessionInfo() > R version 2.15.1 (2012-06-22) > Platform: x86_64-pc-mingw32/x64 (64-bit) > > locale: > [1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United > States.1252 LC_MONETARY=English_United States.1252 > [4] LC_NUMERIC=C LC_TIME=English_United > States.1252 > > attached base packages: > [1] stats graphics grDevices utils datasets methods base > > other attached packages: > [1] NormqPCR_1.4.0 RColorBrewer_1.0-5 ReadqPCR_1.4.0 affy_1.36.1 > Biobase_2.18.0 BiocGenerics_0.4.0 > > loaded via a namespace (and not attached): > [1] affyio_1.26.0 BiocInstaller_1.8.3 preprocessCore_1.20.0 > zlibbioc_1.4.0 > > -- > Sent via the guest posting facility at bioconductor.org. > > _______________________________________________ > Bioconductor mailing list > Bioconductor@r-project.org > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: > http://news.gmane.org/gmane.science.biology.informatics.conductor > -- Dr James R Perkins Institute of Structural and Molecular Biology Division of Biosciences University College London Gower Street London, WC1E 6BT UK email: j.perkins@ucl.ac.uk -- Dr James R Perkins Institute of Structural and Molecular Biology Division of Biosciences University College London Gower Street London, WC1E 6BT UK email: j.perkins@ucl.ac.uk On 28 February 2013 20:36, Franklin Johnson [guest] <guest@bioconductor.org>wrote: > > Dear Maintainer, > > I have created my.qPCRBatch object read into R using the ReadqPCR package: > > rownames(exprs(qPCRBatch)) > [1] "actin_14d_TechReps.1" "actin_14d_TechReps.2" "actin_1d_TechReps.1" > "actin_1d_TechReps.2" "actin_3d_TechReps.1" "actin_3d_TechReps.2" > [7] "actin_7d_TechReps.1" "actin_7d_TechReps.2" "lox22_14d_TechReps.1" > "lox22_14d_TechReps.2" "lox22_1d_TechReps.1" "lox22_1d_TechReps.2" > [13] "lox22_3d_TechReps.1" "lox22_3d_TechReps.2" "lox22_7d_TechReps.1" > "lox22_7d_TechReps.2" > > combinedTechReps=combineTechReps(qPCRBatch) > > combinedTechReps > qPCRBatch (storageMode: lockedEnvironment) > assayData: 8 features, 2 samples > element names: exprs > protocolData: none > phenoData > sampleNames: MeJa Triton.X > varLabels: sample > varMetadata: labelDescription > featureData: none > experimentData: use 'experimentData(object)' > Annotation: > > I have also generated the deltaCq values using: > > hkgs="actin_1d" > > qPCRBatch.norm=deltaCq(combinedTechReps, hkgs=hkgs, calc="arith") > > head(exprs(qPCRBatch.norm)) > MeJa Triton.X > actin_14d 0.655 0.260 > actin_1d 0.000 0.000 > actin_3d -0.120 0.095 > actin_7d 0.465 0.145 > lox22_14d 2.755 3.530 > lox22_1d 0.735 2.740 > > Now, to advance to Section 5.3, do I need to use qPCRBatch.norm. Or, did R > populate qPCRBatch object with this deltaCq data? In other words, for > Section 5.3, does the deltaDeltaCq function calculate deltaDeltaCq using > deltaCq obtained in 5.1, or does it calculate deltaDeltaCq from the raw Cq > data? > > However, I get error message when advancing from Section 5.1 to 5.3 using > qPCRBatch.norm: > > contM<-cbind(c(0,0,0,0,1,1,1,1), c(1,1,1,1,0,0,0,0)) > > colnames(contM)=c("MeJa", "Triton.X") > > rownames(contM)=rownames(exprs(qPCRBatch.norm)) > > contM > MeJa Triton.X > actin_14d 0 1 > actin_1d 0 1 > actin_3d 0 1 > actin_7d 0 1 > lox22_14d 1 0 > lox22_1d 1 0 > lox22_3d 1 0 > lox22_7d 1 0 > > hkgs<-"actin_1d" > > ddCq.norm=deltaDeltaCq(qPCRBatch.norm, maxNACase=0, maxNAControl=0, > hkgs=hkgs, contrastM=contM, case="MeJa", control="Triton.X", > statCalc="geom") > Error in .local(qPCRBatch, ...) : subscript out of bounds > > I tried many attempts to alter the subscripts to no success. So, I > attempted to use the vignette to see how to work with the data. However, I > got the same result: > > head(exprs(qPCRBatch.norm)) > fp1.day3.v fp2.day3.v fp5.day3.mia fp6.day3.mia > fp.3.day.3.v fp.4.day.3.v fp.7.day.3.mia fp.8.day.3.mia > Actb.Rn00667869_m1 0.000000 0.000000 0.000000 0.000000 > 0.000000 0.000000 0.000000 0.000000 > Adipoq.Rn00595250_m1 0.016052 -0.116520 2.933523 2.540987 > -0.178971 -0.563263 2.458509 2.736475 > Adrbk1.Rn00562822_m1 NA NA 6.566628 6.642561 > NA NA 3.737100 6.873568 > Agtrl1.Rn00580252_s1 4.899380 5.035841 6.397364 5.680837 > 5.220796 4.425364 4.794776 5.345202 > Alpl.Rn00564931_m1 12.531942 11.808657 13.035166 12.239549 > 12.394802 11.772896 12.110000 12.255186 > B2m.Rn00560865_m1 0.741558 0.890717 2.040470 2.234605 > 0.505516 0.877598 1.927563 1.903269 > > contM<-cbind(c(0,0,1,1,0,0,1,1), c(1,1,0,0,1,1,0,0)) > > colnames(contM)<-c("interestingPhenotype", "wildTypePhenotype") > > rownames(contM)=sampleNames(qPCRBatch.taqman) > > contM > interestingPhenotype wildTypePhenotype > fp1.day3.v 0 1 > fp2.day3.v 0 1 > fp5.day3.mia 1 0 > fp6.day3.mia 1 0 > fp.3.day.3.v 0 1 > fp.4.day.3.v 0 1 > fp.7.day.3.mia 1 0 > fp.8.day.3.mia 1 0 > > hkg="Actb-Rn00667869_m1" > > ddCq.grr<-deltaDeltaCq(qPCRBatch.norm, hkgs=hkg, contrastM=contM, > case="interestingPhentype", control="wildTypePhenotype", > + statCalc="arith") > Error in .local(qPCRBatch, ...) : subscript out of bounds > > I also made attempts to change this subscript as well, e.g. hkg<=>hkgs, > removed hkgCalc since only using one hkg, but to no success. > > Also, I see for the qPCR.TechReps.txt.example there is a control gene for > each the case detector, respectively. > Unfortunately, you geNorm and NormFinder with example.taqman. However, for > the qPCRBatch.TechReps.example-type of datafile-, which detector do you > choose to normalize the data? In other words, how do you set up your > contrast matrix to match caseA vs. caseB vs. control? > I assume I could do this with the contrast matrix using cbind(c(caseA), > (caseB), (control)), but would NormqPCR::deltaDeltaCq understand this > language? > > Lastly, how to deal with various timepoints: > I have 3 different biological collections: > 1) 1.5, 2) 2, and 3) 3.5. > Two samples per collection (control, treated), and testing only 12 > individual genes plus actin as control gene in each sample and biological > rep, which data for each gene has 4 (1day, 3day, 7day, and 14day) > timepoints (in both control and treated samples as well as for target and > control genes). > Case Control > actin_14d 0 1 > actin_1d 0 1 > actin_3d 0 1 > actin_7d 0 1 > lox22_14d 1 0 > lox22_1d 1 0 > lox22_3d 1 0 > lox22_7d 1 0 > > Right now, I'm only utilizing one data file(one sample): Biological > collection at 1.5. In this file I have both reference genes and the > respective target genes for each timepoint(as shown above). For > deltaDeltaCq function, do I need a second file to compare 1.5 with (e.g. 2 > and/or 3.5), because I'm currently using the featureNames() and not the > sampleNames()? > So, getting an error? This is not logical since I got same error with the > NormqPCR vignette. > > Any suggestions is greatly appreciated. > Regards, > Franklin > > -- output of sessionInfo(): > > > sessionInfo() > R version 2.15.1 (2012-06-22) > Platform: x86_64-pc-mingw32/x64 (64-bit) > > locale: > [1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United > States.1252 LC_MONETARY=English_United States.1252 > [4] LC_NUMERIC=C LC_TIME=English_United > States.1252 > > attached base packages: > [1] stats graphics grDevices utils datasets methods base > > other attached packages: > [1] NormqPCR_1.4.0 RColorBrewer_1.0-5 ReadqPCR_1.4.0 affy_1.36.1 > Biobase_2.18.0 BiocGenerics_0.4.0 > > loaded via a namespace (and not attached): > [1] affyio_1.26.0 BiocInstaller_1.8.3 preprocessCore_1.20.0 > zlibbioc_1.4.0 > > -- > Sent via the guest posting facility at bioconductor.org. > > _______________________________________________ > Bioconductor mailing list > Bioconductor@r-project.org > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: > http://news.gmane.org/gmane.science.biology.informatics.conductor > -- Dr James R Perkins Institute of Structural and Molecular Biology Division of Biosciences University College London Gower Street London, WC1E 6BT UK email: j.perkins@ucl.ac.uk [[alternative HTML version deleted]]