[BioC] ReadqPCR: [[hkgs,]] incorrect number of dimensions

[Franklin Johnson [guest]]

Dear James,

Thanks for your time and help with ReadqPCR and NormqPCR. 

I have worked a bit more with this NormqPCR;
Very useful package, especially, for normalizing raw Ct data, determining housekeeping genes, etc.

Thus far, I have been successful in working through the vignette. Although, I have one last inquiry.
In order to confirm where the error is coming from, I have deduced my input file containing the raw Cq values to 2 conditions, 8 detectors, one technical replication. 

> qPCRBatch=read.qPCR(qPCRBatch.lv)
Warning message:
In read.qPCR(qPCRBatch.lv) :
  Incompatible phenoData object. Created a new one using sample name data derived from raw data.

> exprs(qPCRBatch)
      caseA control
actin 20.89   20.91
lox22 21.36   20.50
lox23 20.93   21.00
lox34 20.89   20.80
lox61 19.50   19.50
lox62 21.00   25.00
lox69 19.30   15.00
lox99 21.10   28.00

> contM=cbind(c(1,0), c(0,1))
> colnames(contM)=c("interest", "no interest")
> rownames(contM)=sampleNames(qPCRBatch.lv)
> contM
        interest no interest
caseA          1           0
control        0           1

> hkgs="actin"
> ddCq.lv=deltaDeltaCq(qPCRBatch.lv, maxNACase=1, maxNAControl=1, hkgs=hkgs, contrastM=contM, case="interest", control="no interest", statCalc="arith", hkgCalc="arith")
Error in caseM[hkgs[1], ] : incorrect number of dimensions

Apart from the vignette, I didn't think I would need to identify hkgs in each sample??

What is odd is that I can complete the deltaCq function,
> qPCRBatch.dcq=deltaCq(qPCRBatch.lv, hkgs=hkgs, calc="arith")
> exprs(qPCRBatch.dcq)
      caseA control
actin  0.00    0.00
lox22  0.47   -0.41
lox23  0.04    0.09
lox34  0.00   -0.11
lox61 -1.39   -1.41
lox62  0.11    4.09
lox69 -1.59   -5.91
lox99  0.21    7.09

, but not the deltaDeltaCq function. 
This says to me that there is something wrong with my "case" vs. "control" comparison in the contrast matrix? However, like the vignette, I have my hkgs genes in both samples, as required by the same detectors for all samples requisite(which makes sense). 

Anyhow, it's been great to work with NormqPCR.
Hopefully, I can complete it by getting the deltaDeltaCq output. 

If you have a chance, can you please take a look at the scripts and correct me where I'm wrong. 

Respectfully,
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] limma_3.14.0       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 tools_2.15.1          zlibbioc_1.4.0   

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