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Zach Roe
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10
@zach-roe-11189
Last seen 4.5 years ago
I have EPIC IDAT files, when I load them using importMethyIDAT, 2 files are detected as HumanMethylation27 samples and 6 files as HumanMethylation450 samples.
What could be causing the incorrect detection of EPIC arrays? I have used this code prior to import 450K IDAT files.
> # Load Illumina EPIC sample map
> idat_fileAnno <- read.csv(file.path(getwd(), 'idat_files_test', 'MiyanoShalabiEPIC_idat_fileAnno_test.csv'), header = T, stringsAsFactors = F)
> # Import Data
> methylData.EPIC <- importMethyIDAT(sampleInfo=idat_fileAnno, dataPath='idat_files')
2 HumanMethylation27 samples found
6 HumanMethylation450 samples found
Error in methylumIDAT(barcodes = barcodes, pdat = pdat, parallel = parallel, :
Cannot process both platforms simultaneously; please run separately.
> sessionInfo()
R version 3.5.0 (2018-04-23)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS Sierra 10.12.6
Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRlapack.dylib
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] splines stats4 parallel stats graphics grDevices utils datasets methods base
other attached packages:
[1] IlluminaHumanMethylationEPICanno.ilm10b4.hg19_0.6.0 IlluminaHumanMethylationEPICanno.ilm10b3.hg19_0.6.0
[3] IlluminaHumanMethylationEPICanno.ilm10b2.hg19_0.6.0 lumi_2.32.0
[5] ChAMP_2.10.2 IlluminaHumanMethylationEPICmanifest_0.3.0
[7] Illumina450ProbeVariants.db_1.16.0 DMRcate_1.16.0
[9] DMRcatedata_1.16.0 DSS_2.28.0
[11] bsseq_1.16.1 FEM_3.8.0
[13] graph_1.58.2 org.Hs.eg.db_3.6.0
[15] impute_1.54.0 igraph_1.2.5
[17] corrplot_0.84 marray_1.58.0
[19] limma_3.36.5 Matrix_1.2-18
[21] AnnotationDbi_1.42.1 ChAMPdata_2.12.0
[23] minfi_1.26.2 bumphunter_1.22.0
[25] locfit_1.5-9.1 iterators_1.0.12
[27] foreach_1.5.0 Biostrings_2.48.0
[29] XVector_0.20.0 SummarizedExperiment_1.10.1
[31] DelayedArray_0.6.6 BiocParallel_1.14.2
[33] matrixStats_0.56.0 GenomicRanges_1.32.7
[35] GenomeInfoDb_1.16.0 IRanges_2.14.12
[37] S4Vectors_0.18.3 reshape2_1.4.3
[39] scales_1.1.0 Biobase_2.40.0
[41] BiocGenerics_0.26.0
loaded via a namespace (and not attached):
[1] R.utils_2.9.2 tidyselect_1.0.0
[3] RSQLite_2.2.0 htmlwidgets_1.5.1
[5] combinat_0.0-8 grid_3.5.0
[7] munsell_0.5.0 codetools_0.2-16
[9] preprocessCore_1.42.0 nleqslv_3.3.2
[11] statmod_1.4.34 fastICA_1.2-2
[13] colorspace_1.4-1 BiocInstaller_1.30.0
[15] knitr_1.28 rstudioapi_0.11
[17] JADE_2.0-2 isva_1.9
[19] GenomeInfoDbData_1.1.0 bit64_0.9-7
[21] rhdf5_2.24.0 vctrs_0.2.4
[23] xfun_0.13 biovizBase_1.28.2
[25] doParallel_1.0.15 R6_2.4.1
[27] clue_0.3-57 illuminaio_0.22.0
[29] AnnotationFilter_1.4.0 bitops_1.0-6
[31] reshape_0.8.8 assertthat_0.2.1
[33] promises_1.1.0 IlluminaHumanMethylation450kanno.ilmn12.hg19_0.6.0
[35] nnet_7.3-13 gtable_0.3.0
[37] affy_1.58.0 methylumi_2.26.0
[39] sva_3.28.0 ensembldb_2.4.1
[41] rlang_0.4.5 genefilter_1.62.0
[43] rtracklayer_1.40.6 lazyeval_0.2.2
[45] acepack_1.4.1 GEOquery_2.48.0
[47] dichromat_2.0-0 checkmate_2.0.0
[49] BiocManager_1.30.10 yaml_2.2.1
[51] GenomicFeatures_1.32.3 backports_1.1.5
[53] httpuv_1.5.2 qvalue_2.12.0
[55] Hmisc_4.3-1 tools_3.5.0
[57] nor1mix_1.3-0 ggplot2_3.3.0
[59] affyio_1.50.0 RColorBrewer_1.1-2
[61] DNAcopy_1.54.0 siggenes_1.54.0
[63] Rcpp_1.0.4 plyr_1.8.6
[65] ROC_1.56.0 base64enc_0.1-3
[67] progress_1.2.2 zlibbioc_1.26.0
[69] purrr_0.3.3 RCurl_1.98-1.1
[71] BiasedUrn_1.07 prettyunits_1.1.1
[73] rpart_4.1-15 openssl_1.4.1
[75] viridis_0.5.1 cluster_2.1.0
[77] magrittr_1.5 data.table_1.12.8
[79] goseq_1.32.0 wateRmelon_1.24.0
[81] ProtGenerics_1.12.0 missMethyl_1.14.0
[83] RPMM_1.25 evaluate_0.14
[85] mime_0.9 hms_0.5.3
[87] xtable_1.8-4 globaltest_5.34.1
[89] XML_3.99-0.3 mclust_5.4.5
[91] gridExtra_2.3 compiler_3.5.0
[93] biomaRt_2.36.1 tibble_2.1.3
[95] KernSmooth_2.23-16 crayon_1.3.4
[97] R.oo_1.23.0 htmltools_0.4.0
[99] later_1.0.0 mgcv_1.8-31
[101] Formula_1.2-3 tidyr_1.0.2
[103] DBI_1.1.0 geneLenDataBase_1.16.0
[105] MASS_7.3-51.5 readr_1.3.1
[107] permute_0.9-5 cli_2.0.2
[109] quadprog_1.5-8 R.methodsS3_1.8.0
[111] Gviz_1.24.0 pkgconfig_2.0.3
[113] GenomicAlignments_1.16.0 IlluminaHumanMethylation450kmanifest_0.4.0
[115] foreign_0.8-76 plotly_4.9.2.1
[117] xml2_1.2.5 annotate_1.58.0
[119] rngtools_1.5 multtest_2.36.0
[121] beanplot_1.2 ruv_0.9.7.1
[123] doRNG_1.8.2 stringr_1.4.0
[125] VariantAnnotation_1.26.1 digest_0.6.25
[127] rmarkdown_2.1 base64_2.0
[129] htmlTable_1.13.3 dendextend_1.13.4
[131] DelayedMatrixStats_1.2.0 curl_4.3
[133] shiny_1.4.0.2 Rsamtools_1.32.3
[135] gtools_3.8.1 jsonlite_1.6.1
[137] lifecycle_0.2.0 nlme_3.1-145
[139] Rhdf5lib_1.2.1 viridisLite_0.3.0
[141] askpass_1.1 BSgenome_1.48.0
[143] fansi_0.4.1 pillar_1.4.3
[145] lattice_0.20-40 fastmap_1.0.1
[147] httr_1.4.1 survival_3.1-11
[149] GO.db_3.6.0 glue_1.3.2
[151] shinythemes_1.1.2 bit_1.1-15.2
[153] stringi_1.4.6 HDF5Array_1.8.1
[155] blob_1.2.1 latticeExtra_0.6-28
[157] memoise_1.1.0 dplyr_0.8.5
