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Hello, I know similar questions have been posted for the cpg.annotate() function in DMRcate() for DMR analysis with EPIC array data (no bisulphite sequencing), but I am really stuck and would massively appreciate any help!
Code should be placed in three backticks as shown below
myannotation <- cpg.annotate("array", MSw, arraytype = "EPIC", analysis.type="differential", design=design, coef=2)
### returning error below
Error in if (nsig == 0) { : missing value where TRUE/FALSE needed
In addition: Warning messages:
1: In logit2(assay(object, "Beta")) : NaNs produced
2: In logit2(assay(object, "Beta")) : NaNs produced
3: Partial NA coefficients for 123812 probe(s)
##the MSw object was produced with the following code and looks as such:
MSw <- getM(MsetSw, type = "beta", betaThreshold = 0.001)
![MSw table][1]
sessionInfo( )
R version 4.2.2 (2022-10-31 ucrt)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19044)
Matrix products: default
locale:
[1] LC_COLLATE=English_United Kingdom.utf8
[2] LC_CTYPE=English_United Kingdom.utf8
[3] LC_MONETARY=English_United Kingdom.utf8
[4] LC_NUMERIC=C
[5] LC_TIME=English_United Kingdom.utf8
attached base packages:
[1] parallel stats4 stats graphics grDevices utils datasets
[8] methods base
other attached packages:
[1] DMRcate_2.12.0
[2] circlize_0.4.15
[3] reshape2_1.4.4
[4] plyr_1.8.8
[5] corpcor_1.6.10
[6] CpGassoc_2.60
[7] data.table_1.14.8
[8] qqman_0.1.8
[9] tidyr_1.3.0
[10] pvclust_2.2-0
[11] sqldf_0.4-11
[12] RSQLite_2.3.1
[13] gsubfn_0.7
[14] proto_1.0.0
[15] pcaMethods_1.90.0
[16] sva_3.46.0
[17] BiocParallel_1.32.6
[18] genefilter_1.80.3
[19] mgcv_1.8-42
[20] nlme_3.1-162
[21] dplyr_1.1.1
[22] limma_3.54.2
[23] WGCNA_1.72-1
[24] fastcluster_1.2.3
[25] dynamicTreeCut_1.63-1
[26] GO.db_3.16.0
[27] AnnotationDbi_1.60.2
[28] missMethyl_1.32.1
[29] IlluminaHumanMethylationEPICanno.ilm10b4.hg19_0.6.0
[30] MatrixEQTL_2.3
[31] IlluminaHumanMethylation450kanno.ilmn12.hg19_0.6.1
[32] IlluminaHumanMethylation450kmanifest_0.4.0
[33] FlowSorted.Blood.EPIC_2.2.0
[34] ExperimentHub_2.6.0
[35] AnnotationHub_3.6.0
[36] BiocFileCache_2.6.1
[37] dbplyr_2.3.2
[38] FlowSorted.Blood.450k_1.36.0
[39] IlluminaHumanMethylationEPICanno.ilm10b2.hg19_0.6.0
[40] IlluminaHumanMethylationEPICmanifest_0.3.0
[41] minfi_1.44.0
[42] bumphunter_1.40.0
[43] locfit_1.5-9.7
[44] iterators_1.0.14
[45] foreach_1.5.2
[46] Biostrings_2.66.0
[47] XVector_0.38.0
[48] SummarizedExperiment_1.28.0
[49] Biobase_2.58.0
[50] MatrixGenerics_1.10.0
[51] matrixStats_0.63.0
[52] GenomicRanges_1.50.2
[53] GenomeInfoDb_1.34.9
[54] IRanges_2.32.0
[55] S4Vectors_0.36.2
[56] BiocGenerics_0.44.0
loaded via a namespace (and not attached):
[1] rappdirs_0.3.3 rtracklayer_1.58.0
[3] R.methodsS3_1.8.2 ggplot2_3.4.2
[5] bit64_4.0.5 knitr_1.42
[7] DelayedArray_0.23.2 R.utils_2.12.2
[9] rpart_4.1.19 KEGGREST_1.38.0
[11] RCurl_1.98-1.12 GEOquery_2.66.0
[13] AnnotationFilter_1.22.0 doParallel_1.0.17
[15] generics_0.1.3 GenomicFeatures_1.50.4
[17] preprocessCore_1.60.2 chron_2.3-60
[19] bit_4.0.5 tzdb_0.3.0
[21] xml2_1.3.3 httpuv_1.6.9
[23] xfun_0.38 hms_1.1.3
[25] evaluate_0.20 promises_1.2.0.1
[27] fansi_1.0.4 restfulr_0.0.15
[29] scrime_1.3.5 progress_1.2.2
[31] DBI_1.1.3 htmlwidgets_1.6.2
[33] reshape_0.8.9 purrr_1.0.1
[35] ellipsis_0.3.2 backports_1.4.1
[37] permute_0.9-7 calibrate_1.7.7
[39] annotate_1.76.0 biomaRt_2.54.1
[41] deldir_1.0-6 sparseMatrixStats_1.10.0
[43] vctrs_0.6.2 ensembldb_2.22.0
[45] cachem_1.0.7 Gviz_1.42.1
[47] BSgenome_1.66.3 checkmate_2.1.0
[49] GenomicAlignments_1.34.1 prettyunits_1.1.1
[51] mclust_6.0.0 cluster_2.1.4
[53] lazyeval_0.2.2 crayon_1.5.2
[55] edgeR_3.40.2 pkgconfig_2.0.3
[57] ProtGenerics_1.30.0 nnet_7.3-18
[59] rlang_1.1.0 lifecycle_1.0.3
[61] filelock_1.0.2 dichromat_2.0-0.1
[63] tcltk_4.2.2 rngtools_1.5.2
[65] base64_2.0.1 Matrix_1.5-4
[67] Rhdf5lib_1.20.0 base64enc_0.1-3
[69] GlobalOptions_0.1.2 png_0.1-8
[71] rjson_0.2.21 bitops_1.0-7
[73] R.oo_1.25.0 rhdf5filters_1.10.1
[75] blob_1.2.4 DelayedMatrixStats_1.20.0
[77] doRNG_1.8.6 shape_1.4.6
[79] stringr_1.5.0 nor1mix_1.3-0
[81] readr_2.1.4 jpeg_0.1-10
[83] scales_1.2.1 memoise_2.0.1
[85] magrittr_2.0.3 zlibbioc_1.44.0
[87] compiler_4.2.2 BiocIO_1.8.0
[89] RColorBrewer_1.1-3 illuminaio_0.40.0
[91] DSS_2.46.0 Rsamtools_2.14.0
[93] cli_3.6.1 htmlTable_2.4.1
[95] Formula_1.2-5 MASS_7.3-58.3
[97] tidyselect_1.2.0 stringi_1.7.12
[99] yaml_2.3.7 askpass_1.1
[101] latticeExtra_0.6-30 grid_4.2.2
[103] VariantAnnotation_1.44.1 tools_4.2.2
[105] rstudioapi_0.14 foreign_0.8-84
[107] bsseq_1.34.0 gridExtra_2.3
[109] digest_0.6.31 BiocManager_1.30.20
[111] shiny_1.7.4 quadprog_1.5-8
[113] Rcpp_1.0.10 siggenes_1.72.0
[115] BiocVersion_3.16.0 later_1.3.0
[117] org.Hs.eg.db_3.16.0 httr_1.4.5
[119] biovizBase_1.46.0 colorspace_2.1-0
[121] XML_3.99-0.14 splines_4.2.2
[123] statmod_1.5.0 multtest_2.54.0
[125] xtable_1.8-4 R6_2.5.1
[127] Hmisc_5.0-1 pillar_1.9.0
[129] htmltools_0.5.5 mime_0.12
[131] glue_1.6.2 fastmap_1.1.1
[133] interactiveDisplayBase_1.36.0 beanplot_1.3.1
[135] codetools_0.2-19 utf8_1.2.3
[137] lattice_0.21-8 tibble_3.2.1
[139] curl_5.0.0 gtools_3.9.4
[141] openssl_2.0.6 interp_1.1-4
[143] survival_3.5-5 rmarkdown_2.21
[145] munsell_0.5.0 rhdf5_2.42.1
[147] GenomeInfoDbData_1.2.9 HDF5Array_1.26.0
[149] impute_1.72.3 gtable_0.3.3
>
I also get the same error message if I specify what=c("Beta") as an argument :)
Error in if (nsig == 0) { : missing value where TRUE/FALSE needed In addition: Warning messages: 1: In logit2(assay(object, "Beta")) : NaNs produced 2: In logit2(assay(object, "Beta")) : NaNs produced 3: Partial NA coefficients for 123812 probe(s)
I think it could be as the table above, View(MSw), shows that many of my beta values are greater than 1. I am unsure how to fix this.