I am attempting to transform a lumiBatch and got the following warning message:
Warning message:
In lumiT(B.complete.RAW.lumi) :
Too few probes are detectable based on detection p-values!
Iteration method will be used for VST.
I realize that this is a warning and not an error so I could proceed but I would like to know the criteria for triggering the warning. I did not find a description of the "Iteration method" in the lumi documentation ( but may have missed it).
Prior to transformation, I read in the raw data and background corrected with no errors or warnings. Here is the info about the lumiBatch up until the VST:
Summary of data information:
Major Operation History:
[1] submitted finished command lumiVersion
<0 rows> (or 0-length row.names)
Object Information:
LumiBatch (storageMode: lockedEnvironment)
assayData: 47323 features, 26 samples
element names: detection, exprs, se.exprs
protocolData: none
phenoData
sampleNames: 1B 1C ... 6D (26 total)
varLabels: TissueID Time Treatment
varMetadata: labelDescription
featureData: none
experimentData: use 'experimentData(object)'
Annotation:
Control Data: N/A
QC information: Please run summary(x, 'QC') for details!
sessionInfo()
R version 3.1.2 (2014-10-31)
Platform: x86_64-w64-mingw32/x64 (64-bit)
locale:
[1] LC_COLLATE=English_United States.1252
[2] LC_CTYPE=English_United States.1252
[3] LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C
[5] LC_TIME=English_United States.1252
attached base packages:
[1] parallel stats graphics grDevices utils datasets
[7] methods base
other attached packages:
[1] limma_3.22.7 lumi_2.18.0 Biobase_2.26.0
[4] BiocGenerics_0.12.1 dplyr_0.4.3
loaded via a namespace (and not attached):
[1] affy_1.44.0 affyio_1.34.0
[3] annotate_1.44.0 AnnotationDbi_1.28.2
[5] assertthat_0.1 base64_1.1
[7] base64enc_0.1-3 BatchJobs_1.6
[9] BBmisc_1.9 beanplot_1.2
[11] BiocInstaller_1.16.5 BiocParallel_1.0.3
[13] biomaRt_2.22.0 Biostrings_2.34.1
[15] bitops_1.0-6 brew_1.0-6
[17] bumphunter_1.6.0 checkmate_1.6.2
[19] codetools_0.2-14 colorspace_1.2-6
[21] DBI_0.3.1 digest_0.6.8
[23] doRNG_1.6 fail_1.2
[25] foreach_1.4.2 genefilter_1.48.1
[27] GenomeInfoDb_1.2.5 GenomicAlignments_1.2.2
[29] GenomicFeatures_1.18.7 GenomicRanges_1.18.4
[31] grid_3.1.2 htmltools_0.2.6
[33] illuminaio_0.8.0 IRanges_2.0.1
[35] iterators_1.0.7 KernSmooth_2.23-15
[37] lattice_0.20-29 locfit_1.5-9.1
[39] magrittr_1.5 MASS_7.3-44
[41] Matrix_1.2-2 matrixStats_0.14.2
[43] mclust_5.0.2 methylumi_2.12.0
[45] mgcv_1.8-7 minfi_1.12.0
[47] multtest_2.22.0 nleqslv_2.8
[49] nlme_3.1-122 nor1mix_1.2-1
[51] pkgmaker_0.22 plyr_1.8.3
[53] preprocessCore_1.28.0 quadprog_1.5-5
[55] R6_2.1.1 RColorBrewer_1.1-2
[57] Rcpp_0.12.0 RCurl_1.95-4.7
[59] registry_0.3 reshape_0.8.5
[61] rmarkdown_0.8 rngtools_1.2.4
[63] Rsamtools_1.18.3 RSQLite_1.0.0
[65] rtracklayer_1.26.3 S4Vectors_0.4.0
[67] sendmailR_1.2-1 siggenes_1.40.0
[69] splines_3.1.2 stats4_3.1.2
[71] stringi_0.5-5 stringr_1.0.0
[73] survival_2.38-3 tools_3.1.2
[75] XML_3.98-1.3 xtable_1.7-4
[77] XVector_0.6.0 yaml_2.1.13
[79] zlibbioc_1.12.0
Thanks in advance for any advice!
Claire Levy
University of Washing OBGYN/Fred Hutchinson Cancer Research Center VIDD
Seattle, WA
