Hi All,
I am following the code in the Lab: CRMA v2 on 10K tumor data
document to process 147 SNP6.0 arrays. 39 of these arrays are from
females and the rest are males. I am getting the following error
message at the end of circular binary segmentation step:
Exception: Something is wrong with the data. Too many non-finite
values: 36890 (25.2% 20.0%)
at throw(Exception(...))
at throw.default(sprintf(Something is wrong with the data. Too many
non-finite values: %d (%.1f%%
at throw(sprintf(Something is wrong with the data. Too many non-
finite values: %d (%.1f%% %.1f%%)
at getRawCnData.CopyNumberChromosomalModel(this, ceList = ceList,
refList = rfList, chromosome = chro
at getRawCnData(this, ceList = ceList, refList = rfList, chromosome
= chromosome, ..., estimateSd = F
at extractRawCopyNumbers.CopyNumberChromosomalModel(this, array =
array, chromosome = chr)
at extractRawCopyNumbers(this, array = array, chromosome = chr)
at fit.CopyNumberSegmentationModel(this, ..., .retResults = FALSE,
verbose = verbose)
at fit(this, ..., .retResults = FALSE, verbose = verbose)
at plot.CopyNumberSegmentationModel(model, path = path, imageFormat
= png, plotband = plotband, arr
at plot(model, p
The sessionInfo is below:
sessionInfo()
R version 2.11.1 (2010-05-31)
x86_64-pc-mingw32
locale:
[1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United
States.1252
[3] LC_MONETARY=English_United States.1252
LC_NUMERIC=C
[5] LC_TIME=English_United States.1252
attached base packages:
[1] stats graphics grDevices utils datasets methods
base
other attached packages:
[1] RColorBrewer_1.0-2 DNAcopy_1.22.1
sfit_0.1.9 aroma.affymetrix_1.7.0 aroma.apd_0.1.7
[6] affxparser_1.20.0 R.huge_0.2.0
aroma.core_1.7.0 aroma.light_1.16.1 matrixStats_0.2.2
[11] R.rsp_0.4.0R.cache_0.3.0
R.filesets_0.9.0 digest_0.4.2 R.utils_1.5.3
[16] R.oo_1.7.4 R.methodsS3_1.2.1
loaded via a namespace (and not attached):
[1] splines_2.11.1
I am assuming that this error is to the presence of two genders but of
course I could be wrong. Can anyone provide an advice as to how to do
this properly to avoid getting the same error? Should I run the
Vignette: Sex-chromosome bias-corrected reference signals from pooled
average?
Thank you very much for your help...
Mete
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