Convert MethyLumiSet into RGChannelSet (Illumina EPIC methylation data)
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Entering edit mode
Nala • 0
@nala-23339
Last seen 4.0 years ago

Hello,

I am trying to convert a MethyLumiSet I have received into an RGChannelSet to use some minfi functions. I have read in the methylumi vignette that this should be possible as long as the OOB probes are included in the MethyLumiSet (http://bioconductor.org/packages/release/bioc/vignettes/methylumi/inst/doc/methylumi450k.pdf, page 9).

So, following the vignette, I tried this:

myRGSet <- as(myMethyLumiSet, "RGChannelSet")

Which led to the following error:

Fetching coordinates for hg19...
Error in getPlatform(chip) : 
You need to specify either HM27 or HM450 as platform to run

But I am unsure how I should specify the platform, and if this is possible for EPIC in addition to 27K and 450K arrays. Is it? If not, is there any other way of converting a MethyLumiSet into an RGChannelSet?

Best wishes, Nala

sessionInfo() R version 3.6.1 (2019-07-05) Platform: x86_64-pc-linux-gnu (64-bit) Running under: Red Hat Enterprise Linux Server 7.6 (Maipo)

Matrix products: default BLAS: /mnt/254b78b9-76b4-422d-84b1-cc632bff60f7/Software/install/R-3.6.1/lib64/R/lib/libRblas.so LAPACK: /mnt/254b78b9-76b4-422d-84b1-cc632bff60f7/Software/install/R-3.6.1/lib64/R/lib/libRlapack.so

locale: [1] LCCTYPE=enGB.UTF-8 LCNUMERIC=C LCTIME=enGB.UTF-8 LCCOLLATE=enGB.UTF-8
[5] LC
MONETARY=enGB.UTF-8 LCMESSAGES=enGB.UTF-8 LCPAPER=enGB.UTF-8 LCNAME=C
[9] LCADDRESS=C LCTELEPHONE=C LCMEASUREMENT=enGB.UTF-8 LC_IDENTIFICATION=C

attached base packages: [1] stats4 parallel stats graphics grDevices utils datasets methods base

other attached packages: [1] affy1.62.0 methylumi2.30.0 FDb.InfiniumMethylation.hg192.2.0
[4] org.Hs.eg.db
3.8.2 TxDb.Hsapiens.UCSC.hg19.knownGene3.2.2 GenomicFeatures1.36.4
[7] AnnotationDbi1.46.1 ggplot23.2.1 reshape21.4.3
[10] scales
1.0.0 minfi1.30.0 bumphunter1.26.0
[13] locfit1.5-9.1 iterators1.0.12 foreach1.4.7
[16] Biostrings
2.52.0 XVector0.24.0 SummarizedExperiment1.14.1
[19] DelayedArray0.10.0 BiocParallel1.18.1 matrixStats0.54.0
[22] Biobase
2.44.0 GenomicRanges1.36.0 GenomeInfoDb1.20.0
[25] IRanges2.18.2 S4Vectors0.22.0 BiocGenerics_0.30.0

loaded via a namespace (and not attached): [1] nlme3.1-140 bitops1.0-6 bit640.9-7 RColorBrewer1.1-2
[5] progress1.2.2 httr1.4.1 tools3.6.1 doRNG1.7.1
[9] nor1mix1.3-0 affyio1.54.0 R62.4.0 HDF5Array1.12.2
[13] lazyeval0.2.2 colorspace1.4-1 DBI1.0.0 withr2.1.2
[17] tidyselect0.2.5 prettyunits1.0.2 base642.0 bit1.1-14
[21] compiler3.6.1 preprocessCore1.46.0 xml21.2.2 pkgmaker0.27
[25] rtracklayer1.44.3 readr1.3.1 genefilter1.66.0 quadprog1.5-7
[29] askpass1.1 stringr1.4.0 digest0.6.20 Rsamtools2.0.0
[33] illuminaio0.26.0 siggenes1.58.0 GEOquery2.52.0 pkgconfig2.0.2
[37] scrime1.3.5 bibtex0.4.2 limma3.40.6 rlang0.4.5
[41] rstudioapi0.10 RSQLite2.1.2 DelayedMatrixStats1.6.0 mclust5.4.5
[45] dplyr0.8.3 RCurl1.95-4.12 magrittr1.5 GenomeInfoDbData1.2.1
[49] Matrix1.2-17 munsell0.5.0 Rcpp1.0.2 Rhdf5lib1.6.0
[53] lifecycle0.2.0 stringi1.4.3 MASS7.3-51.4 zlibbioc1.30.0
[57] rhdf52.28.0 plyr1.8.4 grid3.6.1 blob1.2.0
[61] crayon1.3.4 lattice0.20-38 splines3.6.1 multtest2.40.0
[65] annotate1.62.0 hms0.5.3 beanplot1.2 pillar1.4.2
[69] rngtools1.4 codetools0.2-16 biomaRt2.40.4 XML3.98-1.20
[73] glue1.3.1 BiocManager1.30.4 data.table1.12.8 vctrs0.2.4
[77] gtable0.3.0 tidyr1.0.2 purrr0.3.3 openssl1.4.1
[81] reshape0.8.8 assertthat0.2.1 xtable1.8-4 survival2.44-1.1
[85] tibble2.1.3 GenomicAlignments1.20.1 registry0.5-1 memoise1.1.0

methylumi minfi microarray epic • 1.2k views
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ugh, yeah that'd require an EPIC mapping. it ought not to be particularly difficult, but honestly I'd suggest just reloading the IDAT files into minfi -- it will be less trouble and label swaps will be easier to catch. Plus then you'll have all of the raw data to work with.

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Entering edit mode

Hi Tim,

Thank you very much for your answer. For some reason, I never got notified about your reply and thought my question went unsanswered. I am sorry about that.

I asked the question because in this case, I had only received the data in a MethyLumiSet and I do not have access to the IDATs. The transfer of only the MethyLumiSet took several days and was not very stable, so receiving the IDATs will be hard. In the end I found a workaround by writing my own code for what I had wanted to do with the RGChannelSet, but if there is an easier way, I would still be interested in knowing :-)

Best wishes, Nala

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