
> As iam basic biologist iam facing problem in each step.

Have you already had a look at some of the R tutorials available?  
Familiarising yourself with the basic data structures and commands in  
R might take a bit of time, but it'll make your life much easier down  
the line. "An Introduction to R" at http://www.r-project.org/ ->  
Manuals is a good place to start. In the HTqPCR installation notes at  
http://www.ebi.ac.uk/bertone/software.html we mention a few other links.

> getting difficulty in understanding error. could u help in getting  
> in details of commands other than the pdfs which we get with this  
> package.

The details of R commands are generally available by typing ? in  
front of the command in the R terminal, such as e.g.

?plotCtOverview

These help pages provide information about all input parameters,  
output formats, details of functions and example of how to run them.  
Together with the package vignettes available through openVignette()  
they form the core of the available BioConductor package  
documentation. I'm afraid that at least for HTqPCR there's nothing  
beyond that. Except of course the archives of the BioConductor  
mailing list... Therefore, please keep all replies to the mailing  
list, so that maybe others in the future can benefit from the  
questions and answers provided here.

> all that i have..
> deepak
>
> > plotCtOverview(raw, genes=g, xlim=c(0,50), groups=files$Treatment,
> + calibrator="Control")
> Error in t(log2(t(M)/cali.mean)) :
>   dims [product 20] do not match the length of object [0]

Did you manage to solve the problem you had previously with reading  
in all 99 samples? If not, it could be that you have <99 samples  
present in the qPCRset object "raw", but 99 different groups listed  
in "files$Treatment". Also, are any of your samples actually labelled  
"Control"? From your previous questions it looks like files$Treatment  
is either "Tumor" or "Normal". In that case you ahve to select one of  
these two as the calibrator, i.e. the sample group you want to  
compare other group(s) against. Please see ?plotCtOverview for the  
explanation of what the different parameters d, and what sort of  
input they require.

HTH
\Heidi


> > traceback()
> 2: t(log2(t(M)/cali.mean))
> 1: plotCtOverview(raw, genes = g, xlim = c(0, 50), groups = files 
> $Treatment,
>        calibrator = "Control")
>
> > sessionInfo()
> R version 2.11.0 (2010-04-22)
> x86_64-pc-mingw32
>
> locale:
> [1] LC_COLLATE=English_India.1252  LC_CTYPE=English_India.1252     
> LC_MONETARY=English_India.1252 LC_NUMERIC=C                    
> LC_TIME=English_India.1252
>
> attached base packages:
> [1] stats     graphics  grDevices utils     datasets  methods   base
>
> other attached packages:
> [1] HTqPCR_1.2.0       limma_3.4.1        RColorBrewer_1.0-2  
> Biobase_2.8.0
>
> loaded via a namespace (and not attached):
> [1] affy_1.26.1           affyio_1.16.0          
> gdata_2.8.0           gplots_2.7.4          gtools_2.6.2           
> preprocessCore_1.10.0 tools_2.11.0
> >
>
>
> On Tue, Jun 1, 2010 at 9:26 PM, Heidi Dvinge <heidi@ebi.ac.uk> wrote:
> Hello Deepak,
>
> On 1 Jun 2010, at 16:21, deepak roshan wrote:
>
>> Dear Sir,
>>
>>
>> Thank you for helps.Again iam facing some problems in raedCtData  
>> step. i changed exFiles$File[c(1:30) it reads 30 sample but when i  
>> change to exFiles$File[c(1:99) then it is showing error. could you  
>> tell me how to read 99 sample or what is the maximum number of sample
>> we can analysis.
>
> As I've mentioned before, there's no inherent limit to how many  
> files can be read in. In your example below you get an error  
> somewhere between file number 30 and 99, indicating that there's  
> some input that readCtData() doesn't expect. It could either be a  
> bug in readCtData, or some issue with one of your files.
>
> To narrow down a bit where the problem is, why don't you try:
>
> for (i in 1:99) {
> 	print(i)
> 	test	<- readCtData(files=exFiles$File[i], path=exPath, n.features  
> = 48, flag = 4, feature = 6, type = 7, position = 3, Ct = 8, header  
> = FALSE, SDS = FALSE, n.data = 1, na.value = 40)
> }
>
> Also, in general using traceback() after an error can help you (/ 
> us) narrow down where the error occurred, in case it's in a sub- 
> function.
>
>> Second question is how to give feature class like in example it is  
>> given featureClass(raw) <- factor(c("Marker", "TF", "Kinase") in  
>> my case it is cyclins and cyclin inhibitors where to change that.
>>
> You can change the featureClass information anywhere along the way,  
> such as right after you read in the data. If you have 48 features  
> for each plate, and for example the first 10 are cyclins and the  
> last 38 cyclin inhibitors, you can say:
>
> featureClass(raw) <- factor(rep(c("Cyclin", "Cyclin_Inhibitor"),  
> times=c(10,38)))
>
> HTH
> \Heidi
>
>> Details of the session is given below
>>
>> Deepak
>>
>>
>> > data(qPCRraw)
>> > data(qPCRpros)
>> > class(qPCRraw)
>>
>> [1] "qPCRset"
>> attr(,"package")
>> [1] ".GlobalEnv"
>>
>> > path <- "F:/HTqPCR/TLDA_modi"
>> > exPath <- "F:/HTqPCR/TLDA_modi"
>> > exFiles <- read.delim(file.path(exPath, "files.txt"))
>> > raw <- readCtData(files=exFiles$File[c(1:30)], path=exPath,  
>> n.features = 48, flag = 4, feature = 6, type = 7, position = 3, Ct  
>> = 8, header = FALSE, SDS = FALSE, n.data = 1, na.value = 40)
>> > raw
>>
>> An object of class "qPCRset"
>> Size:  48 features, 30 samples
>> Feature types:           Endogenous Control, Target
>> Feature names:         CCNF-Hs00171049_m1 RBL2-Hs00180562_m1 CCND1- 
>> Hs00277039_m1 ...
>> Feature classes:
>> Feature categories:      OK, Undetermined
>> Sample names:            Sample4 Sample67 Sample80 ...
>> > raw <- readCtData(files=exFiles$File[c(1:99)], path=exPath,  
>> n.features = 48, flag = 4, feature = 6, type = 7, position = 3, Ct  
>> = 8, header = FALSE, SDS = FALSE, n.data = 1, na.value = 40)
>>
>> Error in out@exprs[, cols] <- apply(data, 2, function(x) as.numeric 
>> (as.character(x))) :
>>   number of items to replace is not a multiple of replacement length
>> > sessionInfo()
>> R version 2.11.0 (2010-04-22)
>> x86_64-pc-mingw32
>>
>> locale:
>> [1] LC_COLLATE=English_India.1252  LC_CTYPE=English_India.1252     
>> LC_MONETARY=English_India.1252 LC_NUMERIC=C                    
>> LC_TIME=English_India.1252
>>
>> attached base packages:
>> [1] stats     graphics  grDevices utils     datasets  methods   base
>>
>> other attached packages:
>> [1] HTqPCR_1.2.0       limma_3.4.1        RColorBrewer_1.0-2  
>> Biobase_2.8.0
>>
>> loaded via a namespace (and not attached):
>> [1] affy_1.26.1           affyio_1.16.0          
>> gdata_2.8.0           gplots_2.7.4          gtools_2.6.2           
>> preprocessCore_1.10.0 tools_2.11.0
>> >
>>
>>
>> On Mon, May 31, 2010 at 6:46 PM, Heidi Dvinge <heidi@ebi.ac.uk>  
>> wrote:
>>>
>>> Dear sir,
>>>
>>> thank you for your all help. iam facing some problems in  
>>> raedCtData step. i have 99 sample but it is deading only 6  
>>> samples.how the sample numbers can be incereased to 99. details  
>>> of the  session is given below
>>>
>>> deepak
>>>
>>> > n.samples <- 99
>>> > readCtData(files = files$File, path = path, n.features = 48,  
>>> flag = 4, feature = 6, type = 7, position = 3, Ct = 8, header =  
>>> FALSE, SDS = FALSE, n.data = 1, samples, na.value = 40)
>>> An object of class "qPCRset"
>>> Size:  48 features, 6 samples
>>> Feature types:           Endogenous Control, Target
>>> Feature names:           CCNF-Hs00171049_m1 RBL2-Hs00180562_m1  
>>> CCND1-Hs00277039_m1 ...
>>> Feature classes:
>>> Feature categories:      OK
>>> Sample names:            Sample1 Sample2 Sample3 ...
>>> Warning message:
>>> In readCtData(files = files$File, path = path, n.features = 48,  :
>>>   Not enough sample names provided; using Sample1, Sample2, ...  
>>> instead
>>>
>>
>> Hello Deepak,
>>
>> there is nothing in readCtData specifying that only 6 samples can  
>> be read. Defining a variable n.samples isn't going to change that,  
>> since you don't actually use this variable anywhere. What matters  
>> here is if your length(files$File) is 99. What does just:
>>
>> > files$File
>>
>> say?
>>
>> In the example data there are only 6 files, but if I read some of  
>> them multiple times, I can say:
>>
>> > exPath <- system.file("exData", package="HTqPCR")
>> > exFiles <- read.delim(file.path(exPath, "files.txt"))
>> > raw <- readCtData(files=exFiles$File[c(1:6,2:5,1:6)], path=exPath)
>> > raw
>> An object of class "qPCRset"
>> Size:  384 features, 16 samples
>> Feature types:		 Endogenous Control, Target
>> Feature names:		 Gene1 Gene2 Gene3 ...
>> Feature classes:	
>> Feature categories:	 OK, Undetermined
>> Sample names:		 sample1 sample2 sample3 ...
>>
>> However, note that you do get a warning message about sample  
>> names.  In your readCtData command, you include "samples". This is  
>> meant to be a character vector of sample names, if you don't want  
>> to use file names as sample names. Have you actually defined a  
>> variable called "samples" anywhere?? If you have your sample names  
>> in e.g. a vector called my.samplenames, then you need to run  
>> readCtData with:
>>
>> readCtData(files = files$File, path = path, n.features = 48, flag  
>> = 4, feature = 6, type = 7, position = 3, Ct = 8, header = FALSE,  
>> SDS = FALSE, n.data = 1, samples=my.samplenames, na.value = 40)
>>
>> If not, then skip the "samples" parameter altogether and say:
>>
>> readCtData(files = files$File, path = path, n.features = 48, flag  
>> = 4, feature = 6, type = 7, position = 3, Ct = 8, header = FALSE,  
>> SDS = FALSE, n.data = 1, na.value = 40)
>>
>> Does that change anything?
>> \Heidi
>>
>>
>>
>>> > head(read.delim(file.path(path, "files.txt")))
>>>           File Treatment
>>> 1  Sample4.txt     Tumor
>>> 2 Sample67.txt     Tumor
>>> 3 Sample80.txt     Tumor
>>> 4 Sample44.txt     Tumor
>>> 5 Sample76.txt     Tumor
>>> 6 Sample94.txt    Normal
>>> > tail(read.delim(file.path(path, "files.txt")))
>>>            File Treatment
>>> 94 Sample37.txt     Tumor
>>> 95 Sample32.txt     Tumor
>>> 96 Sample33.txt     Tumor
>>> 97 Sample34.txt     Tumor
>>> 98 Sample25.txt     Tumor
>>> 99 Sample26.txt    Normal
>>>
>>> > sessionInfo()
>>> R version 2.11.0 (2010-04-22)
>>> i386-pc-mingw32
>>> 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] HTqPCR_1.2.0       limma_3.4.0        RColorBrewer_1.0-2  
>>> Biobase_2.8.0
>>> loaded via a namespace (and not attached):
>>> [1] affy_1.26.1           affyio_1.16.0          
>>> gdata_2.8.0           gplots_2.7.4          gtools_2.6.2           
>>> preprocessCore_1.10.0
>>> [7] tools_2.11.0
>>>
>>>
>>
>>
>>
>>
>> -- 
>> Deepak Roshan V G
>> Laboratory Of Cell Cycle Regulation  &   Molecular Oncology
>> Division of Cancer Research
>> Regional Cancer Centre
>> Thiruvananthapuram
>> Kerala, India 695 011
>
>
>
>
> -- 
> Deepak Roshan V G
> Laboratory Of Cell Cycle Regulation  &   Molecular Oncology
> Division of Cancer Research
> Regional Cancer Centre
> Thiruvananthapuram
> Kerala, India 695 011


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