Entering edit mode
Hello,
I have been using DMRcate for quite sometime now and the code I have runs absolutely perfectly in all my datasets besides one, which throws me the error: Error in approx(x = x, y = i, xout = xout, rule = 2) : need at least two non-NA values to interpolate
I only have 140 DMPs identified for this data and makes me wonder if it is due to the low number of DMPs? Does anyone knows why this error occurs?
DMR <- dmrcate(annotated, lambda=1000, C=2, min.cpgs = 2) #C is an statistical factor, optimal at 2 #minimal number of CpGs that wou would consider to have a DMR default=2
Fitting chr4...
Fitting chr3...
Fitting chr9...
Fitting chr1...
Fitting chr13...
Fitting chr11...
Fitting chr16...
Fitting chrX...
Fitting chr14...
Fitting chr12...
Fitting chr10...
Fitting chr2...
Fitting chr15...
Fitting chr6...
Fitting chr5...
Fitting chr7...
Fitting chr8...
Fitting chr20...
Fitting chr19...
Fitting chr17...
Fitting chr22...
Fitting chr21...
Fitting chr18...
Error in approx(x = x, y = i, xout = xout, rule = 2) :
need at least two non-NA values to interpolate
> View(annotation_overlap_only)
> sessionInfo()
R version 4.3.3 (2024-02-29 ucrt)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19045)
Matrix products: default
locale:
[1] LC_COLLATE=English_Australia.utf8 LC_CTYPE=English_Australia.utf8 LC_MONETARY=English_Australia.utf8
[4] LC_NUMERIC=C LC_TIME=English_Australia.utf8
time zone: Australia/Sydney
tzcode source: internal
attached base packages:
[1] stats4 grid stats graphics grDevices utils datasets methods base
other attached packages:
[1] GenomicRanges_1.54.1 GenomeInfoDb_1.38.7 DMRcatedata_2.20.3 ExperimentHub_2.10.0 AnnotationHub_3.10.0
[6] BiocFileCache_2.10.1 dbplyr_2.4.0 IRanges_2.36.0 S4Vectors_0.40.2 BiocGenerics_0.48.1
[11] DMRcate_2.16.1 ggrepel_0.9.5 kableExtra_1.4.0 pkgload_1.3.4 GGally_2.2.1
[16] reshape2_1.4.4 beeswarm_0.4.0 gplots_3.1.3.1 gtools_3.9.5 echarts4r_0.4.5
[21] mitch_1.14.0 ggvenn_0.1.10 sf_1.0-15 ggVennDiagram_1.5.2 lubridate_1.9.3
[26] forcats_1.0.0 stringr_1.5.1 dplyr_1.1.4 purrr_1.0.2 readr_2.1.5
[31] tidyr_1.3.1 tibble_3.2.1 ggplot2_3.5.0 tidyverse_2.0.0
loaded via a namespace (and not attached):
[1] ProtGenerics_1.34.0 matrixStats_1.2.0
[3] bitops_1.0-7 httr_1.4.7
[5] RColorBrewer_1.1-3 doRNG_1.8.6
[7] tools_4.3.3 backports_1.4.1
[9] utf8_1.2.4 R6_2.5.1
[11] HDF5Array_1.30.1 lazyeval_0.2.2
[13] Gviz_1.46.1 rhdf5filters_1.14.1
[15] permute_0.9-7 withr_3.0.0
[17] prettyunits_1.2.0 gridExtra_2.3
[19] base64_2.0.1 preprocessCore_1.64.0
[21] cli_3.6.2 Biobase_2.62.0
[23] labeling_0.4.3 sass_0.4.8
[25] IlluminaHumanMethylationEPICanno.ilm10b4.hg19_0.6.0 genefilter_1.84.0
[27] askpass_1.2.0 proxy_0.4-27
[29] Rsamtools_2.18.0 systemfonts_1.0.5
[31] foreign_0.8-86 illuminaio_0.44.0
[33] siggenes_1.76.0 svglite_2.1.3
[35] R.utils_2.12.3 dichromat_2.0-0.1
[37] scrime_1.3.5 ggforestplot_0.1.0
[39] BSgenome_1.70.2 limma_3.58.1
[41] readxl_1.4.3 rstudioapi_0.15.0
[43] RSQLite_2.3.5 generics_0.1.3
[45] BiocIO_1.12.0 vroom_1.6.5
[47] Matrix_1.6-5 interp_1.1-6
[49] fansi_1.0.6 abind_1.4-5
[51] R.methodsS3_1.8.2 lifecycle_1.0.4
[53] edgeR_4.0.16 yaml_2.3.8
[55] SummarizedExperiment_1.32.0 rhdf5_2.46.1
[57] SparseArray_1.2.4 blob_1.2.4
[59] promises_1.2.1 crayon_1.5.2
[61] lattice_0.22-5 annotate_1.80.0
[63] GenomicFeatures_1.54.3 KEGGREST_1.42.0
[65] beanplot_1.3.1 pillar_1.9.0
[67] knitr_1.45 rjson_0.2.21
[69] codetools_0.2-19 glue_1.7.0
[71] data.table_1.15.2 vctrs_0.6.5
[73] png_0.1-8 cellranger_1.1.0
[75] IlluminaHumanMethylation450kanno.ilmn12.hg19_0.6.1 gtable_0.3.4
[77] cachem_1.0.8 xfun_0.42
[79] S4Arrays_1.2.0 mime_0.12
[81] survival_3.5-8 iterators_1.0.14
[83] units_0.8-5 statmod_1.5.0
[85] interactiveDisplayBase_1.40.0 ellipsis_0.3.2
[87] nlme_3.1-164 bit64_4.0.5
[89] bsseq_1.38.0 progress_1.2.3
[91] filelock_1.0.3 nor1mix_1.3-2
[93] bslib_0.6.1 KernSmooth_2.23-22
[95] rpart_4.1.23 colorspace_2.1-0
[97] DBI_1.2.2 Hmisc_5.1-1
[99] nnet_7.3-19 tidyselect_1.2.1
[101] bit_4.0.5 compiler_4.3.3
[103] curl_5.2.1 htmlTable_2.4.2
[105] xml2_1.3.6 DelayedArray_0.28.0
[107] rtracklayer_1.62.0 checkmate_2.3.1
[109] scales_1.3.0 caTools_1.18.2
[111] classInt_0.4-10 quadprog_1.5-8
[113] rappdirs_0.3.3 digest_0.6.34
[115] rmarkdown_2.26 GEOquery_2.70.0
[117] XVector_0.42.0 htmltools_0.5.7
[119] pkgconfig_2.0.3 jpeg_0.1-10
[121] base64enc_0.1-3 sparseMatrixStats_1.14.0
[123] MatrixGenerics_1.14.0 highr_0.10
[125] fastmap_1.1.1 ensembldb_2.26.0
[127] rlang_1.1.3 htmlwidgets_1.6.4
[129] shiny_1.8.0 DelayedMatrixStats_1.24.0
[131] farver_2.1.1 jquerylib_0.1.4
[133] jsonlite_1.8.8 mclust_6.1
[135] BiocParallel_1.36.0 R.oo_1.26.0
[137] VariantAnnotation_1.48.1 RCurl_1.98-1.14
[139] magrittr_2.0.3 Formula_1.2-5
[141] GenomeInfoDbData_1.2.11 Rhdf5lib_1.24.2
[143] munsell_0.5.0 Rcpp_1.0.12
[145] viridis_0.6.5 stringi_1.8.3
[147] zlibbioc_1.48.0 MASS_7.3-60.0.1
[149] org.Hs.eg.db_3.18.0 bumphunter_1.44.0
[151] plyr_1.8.9 minfi_1.48.0
[153] ggstats_0.5.1 parallel_4.3.3
[155] deldir_2.0-4 Biostrings_2.70.2
[157] splines_4.3.3 multtest_2.58.0
[159] hms_1.1.3 locfit_1.5-9.9
[161] rngtools_1.5.2 biomaRt_2.58.2
[163] missMethyl_1.36.0 BiocVersion_3.18.1
[165] XML_3.99-0.16.1 evaluate_0.23
[167] latticeExtra_0.6-30 biovizBase_1.50.0
[169] BiocManager_1.30.22 foreach_1.5.2
[171] tzdb_0.4.0 httpuv_1.6.14
[173] openssl_2.1.1 reshape_0.8.9
[175] broom_1.0.5 xtable_1.8-4
[177] restfulr_0.0.15 AnnotationFilter_1.26.0
[179] e1071_1.7-14 later_1.3.2
[181] viridisLite_0.4.2 class_7.3-22
[183] memoise_2.0.1 AnnotationDbi_1.64.1
[185] GenomicAlignments_1.38.2 cluster_2.1.6
[187] timechange_0.3.0
