[BioC] How to format SWAN minfi data for bumphunter?
Lara Park [guest]
guest at bioconductor.org
Tue Jun 25 22:22:54 CEST 2013
Hello,
I am analyzing Illumina 450K DNA methylation array data using the SWAN normalization procedures in minfi and I would like to use the statistical models in bumphunter. The bumphunter vignette indicates that data preprocessed in minfi can be used in bumphunter, however I am having difficulties formatting the SWAN-normalized minfi data properly.
I successfully extracted the chr and pos to run clusterMaker. Below is the code of my attempt to get my minfi data formatted for bumphunter function.
data<-getM(MSet.swan) #MethylSet of SWAN normalized data
layout<-cbind(rep(1,12),rep(c(pd$Sample_Group)))
#3 groups of 4 samples each, pd from pData in minfi
#naming y from the vignette as data
#naming X from the vignette as layout
tab <- bumphunter(data, layout, chr, pos, clust, cutoff=.5)
#Error in S %*% vv : requires numeric/complex matrix/vector arguments
Any help would be much appreciated.
-- output of sessionInfo():
> sessionInfo()
R version 3.0.1 (2013-05-16)
Platform: x86_64-pc-linux-gnu (64-bit)
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=en_US.UTF-8
[4] LC_COLLATE=en_US.UTF-8 LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=C LC_NAME=C LC_ADDRESS=C
[10] LC_TELEPHONE=C LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] parallel stats graphics grDevices utils datasets methods base
other attached packages:
[1] doRNG_1.5.3
[2] rngtools_1.2
[3] pkgmaker_0.16
[4] registry_0.2
[5] IlluminaHumanMethylation450kannotation.ilmn.v1.2_0.1.3
[6] minfiData_0.3.2
[7] IlluminaHumanMethylation450kmanifest_0.4.0
[8] minfi_1.6.0
[9] Biostrings_2.28.0
[10] reshape_0.8.4
[11] plyr_1.8
[12] lattice_0.20-15
[13] Biobase_2.20.0
[14] bumphunter_1.0.0
[15] iterators_1.0.6
[16] foreach_1.4.1
[17] GenomicRanges_1.12.4
[18] IRanges_1.18.1
[19] BiocGenerics_0.6.0
loaded via a namespace (and not attached):
[1] beanplot_1.1 codetools_0.2-8 compiler_3.0.1 digest_0.6.3
[5] grid_3.0.1 illuminaio_0.2.0 itertools_0.1-1 limma_3.16.5
[9] MASS_7.3-26 matrixStats_0.8.1 mclust_4.1 multtest_2.16.0
[13] nor1mix_1.1-4 preprocessCore_1.22.0 RColorBrewer_1.0-5 R.methodsS3_1.4.2
[17] siggenes_1.34.0 splines_3.0.1 stats4_3.0.1 stringr_0.6.2
[21] survival_2.37-4 tools_3.0.1 xtable_1.7-1
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