[BioC] how to set up sampleInfo for methylation array in illumina 450K
guest [guest]
guest at bioconductor.org
Tue Apr 29 19:29:41 CEST 2014
Dear Users,
I tried to use lumi to import the methylation array data from illumina 450k array into R using lumi package, but I could not find the instruction on how to format the sampleInfo file. I just set it as below:
SENTRIX_ID SENTRIX_BARCODE SENTRIX_POSITION Group ART initiation Infection
01A00421_NR056388 8691803116 R01C01 HIV-CTR N None
01A00068_NR056389 8691803116 R02C01 HIV-CTR N None
01A00483_NR056390 8691803116 R03C01 HIV-CTR N None
01A00347_NR056391 8691803116 R04C01 HIV-CTR N None
01A00060_NR056393 8691803116 R05C01 Medium N Pre
01A00065_NR056395 8691803116 R06C01 Medium N Post
01A00113_NR056404 8691803116 R01C02 Medium N Post
01A00079_NR056406 8691803116 R02C02 Medium N Post
After reading the sampleinfo file using read.csv() as below
sampleInfo=read.csv("sampleInfo_12.csv",sep="\t",header=T,stringsAsFactors=F)
I used the function as instructed in the turtorial
My_data=importMethyIDAT(sampleInfo, dataPath = getwd(), lib = NULL, bigMatrix=FALSE, dir.bigMatrix='.')
There is an error message:
Error in importMethyIDAT(sampleInfo, dataPath = getwd(), lib = NULL, bigMatrix = FALSE, :
'SENTRIX_POSITION' and 'SENTRIX_BARCODE' or 'SENTRIX_ID' and are required in 'sampleInfo'!
I don't get it that I already added those required items in the sampleInfo, why does it have this error?
Thanks a lot for the help and I really appreciate it.
-- output of sessionInfo():
> sessionInfo()
R version 3.0.2 (2013-09-25)
Platform: x86_64-apple-darwin10.8.0 (64-bit)
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
attached base packages:
[1] parallel stats graphics grDevices utils datasets methods base
other attached packages:
[1] lumi_2.14.2 BiocInstaller_1.12.1 VariantAnnotation_1.8.13 Rsamtools_1.14.3 Biostrings_2.30.1 GenomicRanges_1.14.4
[7] XVector_0.2.0 IRanges_1.20.7 ggplot2_0.9.3.1 phyloseq_1.6.1 picante_1.6-2 nlme_3.1-117
[13] ape_3.1-1 ade4_1.6-2 knitr_1.5 vegan_2.0-10 lattice_0.20-29 permute_0.8-3
[19] biom_0.3.12 metagenomeSeq_1.5.47 devtools_1.5 gplots_2.13.0 RColorBrewer_1.0-5 matrixStats_0.8.14
[25] limma_3.18.13 Biobase_2.22.0 BiocGenerics_0.8.0
loaded via a namespace (and not attached):
[1] affy_1.40.0 affyio_1.30.0 annotate_1.40.1 AnnotationDbi_1.24.0 base64_1.1 beanplot_1.1
[7] biomaRt_2.18.0 bitops_1.0-6 BSgenome_1.30.0 bumphunter_1.2.0 caTools_1.17 cluster_1.15.2
[13] codetools_0.2-8 colorspace_1.2-4 DBI_0.2-7 dichromat_2.0-0 digest_0.6.4 doRNG_1.6
[19] evaluate_0.5.3 foreach_1.4.2 formatR_0.10 gdata_2.13.3 genefilter_1.44.0 GenomicFeatures_1.14.5
[25] grid_3.0.2 gtable_0.1.2 gtools_3.4.0 httr_0.3 igraph_0.7.1 illuminaio_0.4.0
[31] iterators_1.0.7 itertools_0.1-3 KernSmooth_2.23-12 labeling_0.2 locfit_1.5-9.1 MASS_7.3-31
[37] Matrix_1.1-3 mclust_4.3 memoise_0.2.1 methylumi_2.8.0 mgcv_1.7-29 minfi_1.8.9
[43] multtest_2.18.0 munsell_0.4.2 nleqslv_2.1.1 nor1mix_1.1-4 pkgmaker_0.20 plyr_1.8.1
[49] preprocessCore_1.24.0 proto_0.3-10 R.methodsS3_1.6.1 Rcpp_0.11.1 RCurl_1.95-4.1 registry_0.2
[55] reshape_0.8.5 reshape2_1.4 RJSONIO_1.2-0.1 rngtools_1.2.4 RSQLite_0.11.4 rtracklayer_1.22.7
[61] scales_0.2.4 siggenes_1.36.0 splines_3.0.2 stats4_3.0.2 stringr_0.6.2 survival_2.37-7
[67] tools_3.0.2 whisker_0.3-2 XML_3.95-0.2 xtable_1.7-3 zlibbioc_1.8.0
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