Greetings.
Using wateRmelon (1.6.0) I ran into the following error
Error in betaqn(bn = getBeta(object)) : error in evaluating the argument 'bn' in selecting a method for function 'betaqn': Error in getGreen(rgSet)[getProbeInfo(rgSet, type = "II")$AddressA, ] : subscript out of bounds
with a data set for which this previously worked. This is after a pfilter step which removed 1 sample and 6239 sites.
The betaqn
function works on the object not subjected to pfilter
suggesting that pfilter is producing an object that is not quite aligned. Possibly the list of Green readings is not correctly updated (not obvious since the object is in the environment and the relative parts are not 'exposed').
As noted in one of my answer to myself:
I did some further digging and it turns out the error is with getProbeInfo
(package minfi). It is returning the info for the manifest regardless of the FeatureSet object. Thus the returned subscript vector is always longer than the dimensions of the reduced matrix (after filtering).
The function getGreen
returns a matrix from the pfilter object that has fewer rows than the vector returned by getProbeInfomData.pf, type = "II")$AddressA
.
Now to see when this behavior changed.
Gerard
PS. have sent the maintainer of minfi an e-mail asking about the getProbeInfo behavior.
Current version and sessioninfo. ================================ R version 3.1.2 (2014-10-31) Platform: x86_64-redhat-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] sva_3.12.0 [3] genefilter_1.48.1 [4] mgcv_1.8-4 [5] nlme_3.1-119 [6] wateRmelon_1.6.0 [7] IlluminaHumanMethylation450kanno.ilmn12.hg19_0.2.1 [8] ROC_1.42.0 [9] lumi_2.18.0 [10] methylumi_2.12.0 [11] ggplot2_1.0.0 [12] reshape2_1.4.1 [13] scales_0.2.4 [14] matrixStats_0.13.1 [15] limma_3.22.4 [16] minfi_1.12.0 [17] bumphunter_1.6.0 [18] locfit_1.5-9.1 [19] iterators_1.0.7 [20] foreach_1.4.2 [21] Biostrings_2.34.1 [22] XVector_0.6.0 [23] GenomicRanges_1.18.4 [24] GenomeInfoDb_1.2.4 [25] IRanges_2.0.1 [26] S4Vectors_0.4.0 [27] lattice_0.20-29 [28] Biobase_2.26.0 [29] BiocGenerics_0.12.1 loaded via a namespace (and not attached): [1] affy_1.44.0 affyio_1.34.0 annotate_1.44.0 [4] AnnotationDbi_1.28.1 base64_1.2 base64enc_0.1-2 [7] BatchJobs_1.5 BBmisc_1.9 beanplot_1.2 [10] BiocInstaller_1.16.1 BiocParallel_1.0.3 biomaRt_2.22.0 [13] bitops_1.0-6 brew_1.0-6 checkmate_1.5.1 [16] codetools_0.2-10 colorspace_1.2-4 DBI_0.3.1 [19] digest_0.6.8 doRNG_1.6 fail_1.2 [22] GenomicAlignments_1.2.1 GenomicFeatures_1.18.3 grid_3.1.2 [25] gtable_0.1.2 illuminaio_0.8.0 KernSmooth_2.23-13 [28] MASS_7.3-37 Matrix_1.1-5 mclust_4.4 [31] multtest_2.22.0 munsell_0.4.2 nleqslv_2.5 [34] nor1mix_1.2-0 pkgmaker_0.25.8 plyr_1.8.1 [37] preprocessCore_1.28.0 proto_0.3-10 quadprog_1.5-5 [40] R.methodsS3_1.6.2 RColorBrewer_1.1-2 Rcpp_0.11.4 [43] RCurl_1.96-0 registry_0.2 reshape_0.8.5 [46] rngtools_1.2.4 Rsamtools_1.18.2 RSQLite_1.0.0 [49] rtracklayer_1.26.2 sendmailR_1.2-1 siggenes_1.40.0 [52] splines_3.1.2 stringr_0.6.2 survival_2.37-7 [55] tools_3.1.2 XML_3.98-1.1 xtable_1.8-0 [58] zlibbioc_1.12.0