Dear Rob,

thanks for your indications.
I am afraid I have another question:
I am trying to perform the HMM, integrating the calls confidence  
scores provided by the function CRLMM (from the package oligo).
The object I consider for this purpose contains the 19865 SNP of the  
first chromosome of some 250k NSP chip:

 > chr.cc
HmmSnpSet (storageMode: lockedEnvironment)
assayData: 19865 features, 1 samples
   element names: calls, callsConfidence, cnConfidence, copyNumber,  
predictions
experimentData: use 'experimentData(object)'
phenoData
An object of class "AnnotatedDataFrame"
   sampleNames: normalized-Bf15418-Nsp1.CEL
   varLabels and varMetadata description:
     gender: male/female
featureData
An object of class "AnnotatedDataFrame"
   featureNames: SNP_A-1780272, SNP_A-1780304, ..., SNP_A-4241270   
(19865 total)
   varLabels and varMetadata description:
     dbsnp_rs_id: dbsnp_rs_id
     man_fsetid: man_fsetid
     ...: ...
     fragment_length: fragment_length
     (9 total)
Annotation:  pd.mapping250k.nsp
Hidden States:  deletion normal LOH amplification
distance: TRUE
initialStateProbability:
chromosomeArm:
locationCopyNumber:  0 1 1 1.584963
scaleCopyNumber:  0.3100760 0.3100760 0.3100760 0.3100760
pCHOM:  0.999 0.7 0.999 0.7
log2:  TRUE
copyNumberIce:  FALSE
callsIce:  TRUE

To fit the HMM model I do:

 > chr.hmm <- hmm(chr.cc,verbose = TRUE)

which gives the following error

[1] "Fitting HMM to chromosome 1"
[1] "   processing  p  arm of sample normalized-Bf15418-Nsp1.CEL  ..."
Error en callEmission(object, P.CHOM.LOH = pCHOM[1], P.CHOM.Normal =  
pCHOM[2],  :
   Confidence estimates for genotype calls are only supported for the  
50k and 250k Affymetrix SNP chips.
   The slot annotation must contain one of the following identifiers:  
mapping50k.xba240, mapping50k.hind240, mapping100k,  mapping250k.nsp,  
mapping250k.sty, or mapping500k

Then, I change the annotation value and when I fit again the Markov  
model I get the error

 > annotation(chr.cc)="mapping250k.nsp"
 > chr.hmm <- hmm(chr.cc,verbose = TRUE)
[1] "Fitting HMM to chromosome 1"
[1] "   processing  p  arm of sample normalized-Bf15418-Nsp1.CEL  ..."
Error en hapmapP[[1]] : subíndice fuera de  los límites

Have you any idea bout this error.
Note that the model performs fine when "callsIce(chr.cc) ==  FALSE".
Thanks for your help.
Olivier

The traceback and my sessionInfo are:

 > traceback()
13: getCallEmission(object = object[, SAMPLE], hapmapP = hapmapP[[1]],
         P.CHOM.Normal = P.CHOM.Normal, P.CHOM.LOH = P.CHOM.LOH)
12: callEmission(object, P.CHOM.LOH = pCHOM[1], P.CHOM.Normal = pCHOM 
[2],
         SAMPLE = 1)
11: calculateEmissionProbability(obj)
10: calculateEmissionProbability(obj)
9: .local(object, ...)
8: byArm(parm, verbose = verbose, MISSING.CODE = MISSING.CODE, arm =  
"p",
        SCALE = SCALE)
7: byArm(parm, verbose = verbose, MISSING.CODE = MISSING.CODE, arm =  
"p",
        SCALE = SCALE)
6: .local(object, ...)
5: hmmBySample(objList[[i]], verbose = verbose, MISSING.CODE =  
MISSING.CODE,
        keepEmission = keepEmission, keepLikelihood = keepLikelihood,
        keepTransitionProb = keepTransitionProb, SCALE = SCALE)
4: hmmBySample(objList[[i]], verbose = verbose, MISSING.CODE =  
MISSING.CODE,
        keepEmission = keepEmission, keepLikelihood = keepLikelihood,
        keepTransitionProb = keepTransitionProb, SCALE = SCALE)
3: .local(object, ...)
2: hmm(chr.cc, verbose = TRUE)
1: hmm(chr.cc, verbose = TRUE)
 > sessionInfo()
R version 2.6.0 alpha (2007-09-16 r42884)
i386-apple-darwin8.10.1

locale:
es_ES.UTF-8/es_ES.UTF-8/es_ES.UTF-8/C/es_ES.UTF-8/es_ES.UTF-8

attached base packages:
[1] splines   tools     stats     graphics  grDevices utils      
datasets  methods   base

other attached packages:
[1] RColorBrewer_1.0-1       VanillaICE_0.99.2         
SNPchip_1.1.32           R.utils_0.9.6
[5] R.oo_1.3.0               pd.mapping250k.nsp_0.3.2  
oligo_1.1.22             oligoClasses_0.99.2
[9] affxparser_1.9.5         AnnotationDbi_0.1.15      
preprocessCore_0.99.17   RSQLite_0.6-2
[13] DBI_0.2-3                Biobase_1.15.33

loaded via a namespace (and not attached):
[1] affyio_1.5.11

--  
________________________________________________________________________

Olivier G. Nuñez
nunez@est-econ.uc3m.es
Universidad Carlos III de Madrid [ Tel : +34 663 03 69 09 ]
Departamento de Estadistica [ Fax : +34 91 624 98 49 ]
Facultad de Ciencias Sociales
C/ Madrid 126 GETAFE 28903 SPAIN
Web Page: http://www.est-econ.uc3m.es/onunez

________________________________________________________________________


El 19/09/2007, a las 23:27, Rob Scharpf escribió:

> No.  But you only need to rbind the elements of assayData and  
> featureData.
>
> e.g.,
>
> > merged <- new("HmmSnpSet",
>        	                       copyNumber = rbind(copyNumber(Nsp), 
> copyNumber(Sty)),
>                                 <rbind other assayData elements>,
>                                 <rbind featureData>,
>                                 phenoData=phenoData(Nsp))
>
>
> Then make sure you've created a validObject
>
> validObject(merged)
>
> if you get an error message, make sure the column names in Sty are  
> the same as the column names in Nsp.
>
> If you are using the callsConfidence package, then its a little  
> more tricky and we might have to make sure you're getting the  
> confidence scores that correspond to the chip.  If you are only  
> fitting the Vanilla HMM, then the above should work.
>
> Rob
>
>
>> Dear Rob,
>>
>> I can now analyze the chromosomal abnormalities for my chips under  
>> SNPchip + VanillaICE.
>> Nevertheless, it would be fine to merge the Nsp and Sty  "snp  
>> sets" in order to obtain only one object.
>> Is there exist an easy way to do this under SNPchip.
>> Thanks for your help.
>> Olivier
>>
>>
>> --  
>> _____________________________________________________________________ 
>> ___
>>
>> Olivier G. Nuñez
>> nunez@est-econ.uc3m.es
>> Universidad Carlos III de Madrid [ Tel : +34 663 03 69 09 ]
>> Departamento de Estadistica [ Fax : +34 91 624 98 49 ]
>> Facultad de Ciencias Sociales
>> C/ Madrid 126 GETAFE 28903 SPAIN
>> Web Page: http://www.est-econ.uc3m.es/onunez
>>
>> _____________________________________________________________________ 
>> ___
>>
>>
>> El 17/09/2007, a las 14:49, Rob Scharpf escribió:
>>
>>> Hi Olivier,
>>>
>>>> I eventually decided to create manually the featureData slot,  
>>>> since I got the following new error with getSnpAnnotation:
>>>>
>>>> > getSnpAnnotation(obj)
>>>> Error en sqliteExecStatement(con, statement, bind.data) :
>>>>   RS-DBI driver: (error in statement: String or BLOB exceeded  
>>>> size limit)
>>>
>>>
>>
>


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