Hi Abhi, 

The issue is likely to do with your small (n=3) samples size (less than 8 and our new method, which uses k-means - http://www.biomedcentral.com/1471-2105/15/158/abstract will not be happy). We'll add an error message explaining this to the code. 

If adding a few mores samples doesn't help, perhaps you can provide us with a subset of your idat files (offline) so that we can have a go at reproducing this error. 

Cheers, 

Matt 
----- Original Message -----

From: "Abhishek Pratap" <apratap@sagebase.org> 
To: "Matt Ritchie" <mritchie@wehi.edu.au> 
Cc: bioconductor@r-project.org 
Sent: Friday, 6 June, 2014 6:19:51 AM 
Subject: Re: [BioC] crlmm : copy number and genotyping of Illumina data 

Hey Matt 


Here is the most recent error I got 

Instantiate CNSet container. Initializing container for genotyping and copy number estimation Processing sample stratum 1 of 1 Quantile normalizing 3 arrays, one at a time. |===============================================================================================| 100% Calibrating 3 arrays. |===============================================================================================| 100% Finished preprocessing. Preprocessing complete.  Begin genotyping... Start computing log ratio -- Processing segment 1 out of 9 -- Processing segment 2 out of 9 -- Processing segment 3 out of 9 -- Processing segment 4 out of 9 -- Processing segment 5 out of 9 -- Processing segment 6 out of 9 -- Processing segment 7 out of 9 -- Processing segment 8 out of 9 -- Processing segment 9 out of 9 Done computing log ratio leaving out novariant SNPs Start calculating Prior Means Error in checkForRemoteErrors(val) : 
  8 nodes produced errors; first error: number of cluster centres must lie between 1 and nrow(x) 


On Thu, Jun 5, 2014 at 12:36 PM, Abhishek Pratap < apratap@sagebase.org > wrote: 



Here it is. hopefully the formatting is not that bad 

-A 


> sessionInfo() R version 3.1.0 (2014-04-10)
Platform: x86_64-unknown-linux-gnu (64-bit)

locale:
 [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C         LC_TIME=C            LC_COLLATE=C        
 [5] LC_MONETARY=C        LC_MESSAGES=C        LC_PAPER=C           LC_NAME=C           
 [9] LC_ADDRESS=C         LC_TELEPHONE=C       LC_MEASUREMENT=C     LC_IDENTIFICATION=C 

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

other attached packages:
 [1] synapseClient_1.2-1          affy_1.42.2                  frma_1.16.0                 
 [4] GEOquery_2.30.0              Biobase_2.24.0               RColorBrewer_1.0-5          
 [7] gplots_2.13.0                samr_2.0                     matrixStats_0.8.14          
[10] impute_1.38.1                ggplot2_1.0.0                VennDiagram_1.6.5           
[13] DESeq2_1.4.5                 RcppArmadillo_0.4.300.0      Rcpp_0.11.1                 
[16] GenomicRanges_1.16.3         GenomeInfoDb_1.0.2           IRanges_1.22.7              
[19] BiocGenerics_0.10.0          illuminaio_0.6.0             gdata_2.13.3                
[22] ff_2.2-13                    bit_1.1-12                   humanomni5quadv1bCrlmm_1.0.0
[25] crlmm_1.22.0                 preprocessCore_1.26.1        oligoClasses_1.26.0         
[28] BiocInstaller_1.14.2        

loaded via a namespace (and not attached):
 [1] AnnotationDbi_1.26.0 Biostrings_2.32.0    DBI_0.2-7            KernSmooth_2.23-12  
 [5] MASS_7.3-33          Matrix_1.1-3         R.methodsS3_1.6.1    RCurl_1.95-4.1      
 [9] RJSONIO_1.2-0.2      RSQLite_0.11.4       RcppEigen_0.3.2.1.2  VGAM_0.9-4          
[13] XML_3.98-1.1         XVector_0.4.0        affxparser_1.36.0    affyio_1.32.0       
[17] annotate_1.42.0      base64_1.1           bitops_1.0-6         caTools_1.17        
[21] codetools_0.2-8      colorspace_1.2-4     digest_0.6.4         ellipse_0.3-8       
[25] foreach_1.4.2        genefilter_1.46.1    geneplotter_1.42.0   gtable_0.1.2        
[29] gtools_3.4.1         iterators_1.0.7      lattice_0.20-29      locfit_1.5-9.1      
[33] munsell_0.4.2        mvtnorm_0.9-99992    oligo_1.28.2         plyr_1.8.1          
[37] proto_0.3-10         reshape2_1.4         scales_0.2.4         splines_3.1.0       
[41] stats4_3.1.0         stringr_0.6.2        survival_2.37-7      xtable_1.7-3        
[45] zlibbioc_1.10.0 


On Tue, Jun 3, 2014 at 4:59 PM, Matt Ritchie < mritchie@wehi.edu.au > wrote: 

<blockquote>

Dear Abhi, 

Can you provide your sessionInfo()? 

Thanks, 

Matt 

From: "Abhishek Pratap" < apratap@sagebase.org > 
To: "Matt Ritchie" < mritchie@wehi.edu.au > 
Cc: bioconductor@r-project.org 
Sent: Tuesday, 3 June, 2014 1:36:20 PM 
Subject: Re: [BioC] crlmm : copy number and genotyping of Illumina data 


Hi Matt 

As it happens this got on the back burner earlier and I am getting back to it now. I am getting similar errors trying to do the CNV analysis on Illumina Omni5 idat files. I would be more than happy to share subset of data with you. Just wondering if you would have time now to help with this. 


Depending on the subset of idat files I choose I am getting different errors. 

Example: 

#1 
leaving out novariant SNPs Start calculating Prior Means Error in calculatePriorValues(M, numSNP, verbose) : 
  could not find function "makeCluster" 

#2 
Instantiate CNSet container. Initializing container for genotyping and copy number estimation Processing sample stratum 1 of 1 Quantile normalizing 12 arrays, one at a time. |==========================================================================| 100% Calibrating 12 arrays. |==================                                                        |  25% Error in chol.default(crossprod(sweep(matS, 1, z[, 1], FUN = "*"), matS)) : 
  the leading minor of order 1 is not positive definite In addition: Warning messages: 1: In readIdatFiles(sampleSheet = sampleSheet[sel, ], arrayNames = arrayNames[sel],  :
  Chips are not of the same type.  Skipping 6431_8116121004_R03C01_Grn.idat and 6431_8116121004_R03C01_Red.idat 2: In readIdatFiles(sampleSheet = sampleSheet[sel, ], arrayNames = arrayNames[sel],  :
  Chips are not of the same type.  Skipping 6440_8116121004_R04C01_Grn.idat and 6440_8116121004_R04C01_Red.idat 3: In readIdatFiles(sampleSheet = sampleSheet[sel, ], arrayNames = arrayNames[sel],  :
  Chips are not of the same type.  Skipping 6449_8116121005_R01C01_Grn.idat and 6449_8116121005_R01C01_Red.idat 

Thanks! 
-Abhi 


On Tue, Feb 18, 2014 at 8:28 PM, Matt Ritchie < mritchie@wehi.edu.au > wrote: 

<blockquote>
Dear Abhi, 

You're using the appropriate function. Judging by the warning message, it looks like one of your samples is not like the others (i.e. sample 6431_8116121004 is not Omni5 version 1b). 

Maybe try leaving that one out and re-running? If that doesn't help, perhaps you could put the idat files for this test set of 5 arrays online so that I can take a closer look. 

Best wishes, 

Matt 

----- Original Message ----- 
From: "Abhishek Pratap" < apratap@sagebase.org > 
To: bioconductor@r-project.org 
Sent: Tuesday, 18 February, 2014 11:01:38 AM 
Subject: [BioC] crlmm : copy number and genotyping of Illumina data 

Hi All 

I am trying to use crlmm package for doing the genotyping and CNV 
analysis on a set ~200 samples genotyped on Illumina Omni5 array. 


I tried following the vignette (seems a bit dated) and got some 
errors(see below) 
http://www.bioconductor.org/packages/release/bioc/vignettes/crlmm/inst/doc/IlluminaPreprocessCN.pdf 

Also searching a bit more I found multiple functions in the code of 
crlmm like (genotype.Illumina, crlmmIlluminav2 etc) which seem to be 
doing similar stuff. 

Just wondering if someone can point me to the latest recipe(if any) of 
reading in the idat files (dual channel) and do the basic genotyping 
calling + copy number analysis. 


here is what I have done for a test case (5 arrays) 


> cnSet <- genotype.Illumina(sampleSheet = samplesheet[1:5,], 
+ arrayNames = arrayNames[1:5], 
+ arrayInfoColNames = 
list(barcode="SentrixBarcode_A", position="SentrixPosition_A"), 
+ path = datadir, 
+ copynumber = T, 
+ batch = samplesheet$Sample_Group[1:5], 
+ cdfName = "humanomni5quadv1b", 
+ call.method = "krlmm", 
+ verbose=T 
+ ) 
Instantiate CNSet container. 
Initializing container for genotyping and copy number estimation 
reading /work/DAT_118__AML/Analysis/dset1/CNV/data/5396_6298080101_R02C01_Grn.idat 
reading /work/DAT_118__AML/Analysis/dset1/CNV/data/5405_6298080103_R03C01_Grn.idat 
reading /work/DAT_118__AML/Analysis/dset1/CNV/data/5414_6298098003_R04C01_Grn.idat 
reading /work/DAT_118__AML/Analysis/dset1/CNV/data/6431_8116121004_R03C01_Grn.idat 
reading /work/DAT_118__AML/Analysis/dset1/CNV/data/5423_6762372017_R01C01_Grn.idat 
Processing sample stratum 1 of 1 

Loading chip annotation information. 
Loading reference normalization information. 
Quantile normalizing 5 arrays, one at a time. 
|===============================================================================================| 
100% 
Loading snp annotation and mixture model parameters. 
Calibrating 5 arrays. 
|========================================================= 
| 60% 
Error in quantile.default(M, c(1, 5)/6, names = FALSE) : 
missing values and NaN's not allowed if 'na.rm' is FALSE 

In addition: Warning messages: 
1: In getProtocolData.Illumina(grnidats, sep = sep, fileExt = fileExt$green, : 
Chips are not of the same type. Skipping 6431_8116121004_R03C01_Grn.idat 
2: In readIdatFiles(sampleSheet = sampleSheet[sel, ], arrayNames = 
arrayNames[sel], : 
Chips are not of the same type. Skipping 
6431_8116121004_R03C01_Grn.idat and 6431_8116121004_R03C01_Red.idat 




Thanks! 
-Abhi 

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</blockquote>



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