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.