[BioC] HTqPCR

[Franklin Johnson [guest]]

Dear Heidi,

I am trying to tailor HTqPCR.R such that it can readCtdata into an qPCRSet. I have manually constructed my dataset with 162 gene features, and two technical replicates, generated from 96-well plate. I have formatted the data (162:3) as such col.names=c(feature=1, type=2, Ct=3:
> data<-read.delim("lv_TechRep.1.txt")
> data
    featureNames   featureType    Ct
1          lox22        untreated.0d 22.28
2        actin22        untreated.0d 20.30
3        actin22          control.1d 20.91
4        actin22          control.3d 21.08
5        actin22          control.7d 21.00
6        actin22         control.14d 21.32
7          lox22          control.1d 23.65
8          lox22          control.3d 24.77
9          lox22          control.7d 23.99
10         lox22        control.14d 24.47
11       actin22          treated.1d 21.36
12       actin22          treated.3d 21.22
13       actin22          treated.7d 21.79
14         lox22         treated.14d 22.07
15         lox22         treated.1d 22.13
16         lox22          treated.3d 21.99
17         lox22          treated.7d 24.17
18         lox22         treated.14d 24.17
19         lox23       untreated.0d 24.86
20       actin23        untreated.0d 23.22
21       actin23          control.1d 21.09
22       actin23          control.3d 21.81
23       actin23          control.7d 21.52
24       actin23         control.14d 21.33
25         lox23         control.1d 25.87
26         lox23          control.3d 26.78
27         lox23          control.7d 26.38
28         lox23         control.14d 27.92
29       actin23          treated.1d 21.47
30       actin23          treated.3d 21.35
31       actin23          treated.7d 21.68
32         lox23         treated.14d 22.04
33         lox23          treated.1d 25.77
34         lox23          treated.3d 26.03
35         lox23          treated.7d 27.31
36         lox23         treated.14d 28.11
37         lox28        untreated.0d 23.85
38       actin28        untreated.0d 19.96
39       actin28          control.1d 20.35
40       actin28          control.3d 20.70
41       actin28          control.7d 21.14
42       actin28         control.14d 21.00
43         lox28          control.1d 19.96
44         lox28         control.3d 23.85
45         lox28         control.7d 25.15
46         lox28         control.14d 25.91
....
162....

I've tried to read in the data using 
raw<-readCtData(c("lv_TechRep.1","lv_TechRep.2"), path=path, n.features=162, column.info=(c(flag=NULL, feature=1, type=2, Ct=3, position=NULL)), format="plain", 
header=T, n.data=1))
However, I get error messages:
Error in readCtData(c("lv_TechRep.1.txt", "lv_TechRep.2.txt"), path = NULL,  : 
  argument 7 matches multiple formal arguments

Can I not list the TechReps.n in readCtData prior to combineTechReps?

Does HTqPCR not read my file because of file.dim()? 
I've tried to use ReadqPCR, qPCRNorm and ddCt functions but cannot read CtData into an eSet. I've also tried to read in read.delim and data.frame, then convert this to a matrix(). However, I continue to get error messages when trying to form my rownames:
 rownames(temp)<-paste("gene", 1:162)
Error in `rownames<-`(`*tmp*`, value = c("gene 1", "gene 2", "gene 3",  : 
  length of 'dimnames' [1] not equal to array extent

Any suggestions on the data formatting (both tech.reps are identical except for Ct values) or how to write in the data to make an qPCRSet.

I've seen the previous postings, however, this was not that helpful for my situation. 

Best 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] ddCt_1.12.0         lattice_0.20-13     xtable_1.7-0        NormqPCR_1.4.0      ReadqPCR_1.4.0      affy_1.36.1         BiocInstaller_1.8.3
 [8] HTqPCR_1.12.0       limma_3.14.0        RColorBrewer_1.0-5  Biobase_2.18.0      BiocGenerics_0.4.0 

loaded via a namespace (and not attached):
[1] affyio_1.26.0         gdata_2.12.0          gplots_2.11.0         grid_2.15.1           gtools_2.7.0          preprocessCore_1.20.0
[7] stats4_2.15.1         tools_2.15.1          zlibbioc_1.4.0       


--
Sent via the guest posting facility at bioconductor.org.