hi; Running the 'ChAMP' demo with its test data per vignette instructions ending with :
champ.process(directory = testDir)
all seems to work until this happens:
---
Preparing files for ComBat
Your data is being logit transformed before batch correction
Beginning batch correction
Found 3 batches
Found 1 categorical covariate(s)
Standardizing Data across genes
Fitting L/S model and finding priors
Finding parametric adjustments
Adjusting the Data
Your data is being inverse logit transformed
Run Probe Lasso DMR Hunter
[1] "contrast C T"
You have found 97281 significant MVPs with a BH adjusted P-value below 0.05
You have found 2933 DMRs.
You have found 2761 significant DMRs with a dmr.p < 0.05.
Run champ.CNA
You have chosen Control as the reference and this does not exist in your sample sheet (column Sample_Group). The analysis will run with ChAMP blood controls.
champ.CNA is using the samples you have defined as champCtl as the reference for calculating copy number aberrations.
As you are using the ChAMP controls Combat cannot adjust for batch effects. Batch effects may affect your dataset.
Saving Copy Number information for each Sample
Error in sort(abs(diff(genomdat)))[1:n.keep] :
only 0's may be mixed with negative subscripts
---
Any thoughts?
Thanks
Hamid Bolouri
> traceback()
4: trimmed.variance(genomdat[ina], trim)
3: smooth.CNA(CNA.object)
2: champ.CNA(intensity = myLoad$intensity, pd = myLoad$pd, batchCorrect = batchCorrect,
resultsDir = resultsDir, sampleCNA = sampleCNA, plotSample = plotSample,
groupFreqPlots = groupFreqPlots, freqThreshold = freqThreshold)
1: champ.process(directory = testDir)
---
> sessionInfo()
R version 3.1.2 (2014-10-31)
Platform: x86_64-unknown-linux-gnu (64-bit)
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats4 parallel stats graphics grDevices utils datasets
[8] methods base
other attached packages:
[1] IlluminaHumanMethylation450kmanifest_0.4.0
[2] ChAMP_1.4.0
[3] Illumina450ProbeVariants.db_1.1.1
[4] ChAMPdata_1.1.2
[5] minfi_1.12.0
[6] bumphunter_1.6.0
[7] locfit_1.5-9.1
[8] iterators_1.0.7
[9] foreach_1.4.2
[10] Biostrings_2.34.1
[11] XVector_0.6.0
[12] GenomicRanges_1.18.4
[13] GenomeInfoDb_1.2.4
[14] IRanges_2.0.1
[15] S4Vectors_0.4.0
[16] lattice_0.20-29
[17] Biobase_2.26.0
[18] BiocGenerics_0.12.1
[19] BiocInstaller_1.16.1
loaded via a namespace (and not attached):
[1] annotate_1.44.0 AnnotationDbi_1.28.1 base64_1.1
[4] beanplot_1.2 cluster_1.15.3 codetools_0.2-9
[7] DBI_0.3.1 digest_0.6.4 DNAcopy_1.40.0
[10] doRNG_1.6 genefilter_1.48.1 grid_3.1.2
[13] illuminaio_0.8.0 impute_1.40.0 limma_3.22.1
[16] marray_1.44.0 MASS_7.3-35 Matrix_1.1-4
[19] matrixStats_0.12.2 mclust_4.4 mgcv_1.8-3
[22] multtest_2.22.0 nlme_3.1-118 nor1mix_1.2-0
[25] pkgmaker_0.22 plyr_1.8.1 preprocessCore_1.28.0
[28] quadprog_1.5-5 R.methodsS3_1.6.1 RColorBrewer_1.0-5
[31] Rcpp_0.11.3 registry_0.2 reshape_0.8.5
[34] rngtools_1.2.4 RPMM_1.20 RSQLite_1.0.0
[37] siggenes_1.40.0 splines_3.1.2 stringr_0.6.2
[40] survival_2.37-7 sva_3.12.0 tools_3.1.2
[43] wateRmelon_1.6.0 XML_3.98-1.1 xtable_1.7-4
[46] zlibbioc_1.12.0
I tried to alert the ChAMP maintainer to this thread but my email bounced; if anyone knows how to contact them, let me know.
I did get ahold of the maintainer and advise them about this thread; I hope they will reply soon.