[BioC] Re: concentrations

[Adaikalavan Ramasamy]

1. Don't change the subject line unless absolutely necessary

2. Learn to debug the codes or at least narrow down the problem

3. The authors of SpikeIn names (or later renamed) the array names to be
"0.50", "0.75" etc which is stored as character (as indicated by the
quotes) since names need to be character. You can coerce this to numeric
by using as.numeric() function. I believe that sampleNames(pset1) is
something like "./R/ME_cel/Expt1_R1.CEL" which you cannot coerce into
numerics. See my previous email about extracting info from sample names.

4. I believe the 'concentrations' refers to concentrations of the spike
in genes and are known prior to hybridisation. So you cannot calculate
the 'concentrations' from microarray data.

5. 'ProbeSet' is a class not a name. You cannot turn something into a
'ProbeSet' class by using probeset(). Do you know what probeset() does ?
Have you at least read the documentation for this via help(probeset).

6. To get the PM value, why just do as the example in help(probeset)
suggests ? i.e. pms <- pm( data.raw )

Regards, Adai


On Wed, 2005-06-01 at 17:14 +0200, Mohammad Esad-Djou wrote:
> Hallo all,
> thank you very much for your suggestions.
> 
> > Next time, please learn to ask the question more clearly (with example
> > of the desired output) to avoid the rest of guessing (e.g. what do you
> > mean by "correctly finding numeric values").
> 
> Yes.  You are right. I try to reformulate my question. I would like to compute concentrations for different ProbeSet. 
> I used SpikeIn example in 
> 
> Description of affy
> Laurent Gautier, Rafael Irizarry, Leslie Cope, and Ben Bolstad
> April 21, 2005
> 
> page 22:
> 
> > data(SpikeIn)
> > pms <- pm(SpikeIn)
> > mms <- mm(SpikeIn)
> > par(mfrow = c(1, 2))
> > concentrations <- matrix(as.numeric(sampleNames(SpikeIn)), 20,
> + 12, byrow = TRUE)
> > matplot(concentrations, pms, log = "xy", main = "PM", ylim = c(30,
> + 20000))
> > lines(concentrations[1, ], apply(pms, 2, mean), lwd = 3)
> > matplot(concentrations, mms, log = "xy", main = "MM", ylim = c(30,
> + 20000))
> > lines(concentrations[1, ], apply(mms, 2, mean), lwd = 3)
> 
> 
> I wrote:
> >library(affy)
> >data.raw <- ReadAffy(filenames="./R/ME_cel/Expt1_R1.CEL", ....)
> >pset1 <- probeset(data.raw,geneNames(data.raw)[1])
> 
> Test:
> >pset1
> $"1007_s_at"
> ProbeSet object:
>   id=1007_s_at
>   pm= 16 probes x  4  chips
> 
> and:
> > SpikeIn
> ProbeSet object:
>   id=AFFX-BioB-5_at
>   pm= 20 probes x  12  chips
> 
> R program calls both objects ProbeSet, but I cannot go same way as above example: (e.g.)
> 
> > pms <- pm(pset1)
> Error in pm(pset1) : No direct or inherited method for function "pm" for this call
> 
> > sampleNames(pset1)
> Error in sampleNames(pset1) : No direct or inherited method for function "sampleNames" for this call
> 
> > sampleNames(SpikeIn)
>  [1] "0.50"   "0.75"   "1.00"   "1.50"   "2.00"   "3.00"   "5.00"   "12.50" 
>  [9] "25.00"  "50.00"  "75.00"  "150.00"
> 
> 
> My main question:
> 1. How can I compute concentrations for different ProbeSet?
> 
> 2. What didn't I consider for ProbeSet (SpikeIn and pset1)?
> 
> Thanks,
> Mohammad Esad-Djou
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