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Hi everybody,
I tried CNV-analysis with the conumee package, however, I always get the following error:
*Fehler in .local(query, ref, anno, ...) :
query intensities not given for all probes.*
I've already found some entries with the same problem, but all of them work with the overlapping array type.
As my R skills are quite basic, I would be very happy if someone could help me solve this problem.
Many thanks!
mset
class: MethylSet
dim: 866238 8
metadata(0):
assays(2): Meth Unmeth
rownames(866238): cg18478105 cg09835024 ... cg10633746 cg12623625
rowData names(0):
colnames(8): 204596820115_R01C01 204596820115_R02C01 ... 204596820115_R07C01 204596820115_R08C01
colData names(7): Sample_Name Sample_Group ... Basename filenames
Annotation
array: IlluminaHumanMethylationEPIC
annotation: ilm10b4.hg19
Preprocessing
Method: Illumina, bg.correct = TRUE, normalize = controls, reference = 1
minfi version: 1.36.0
Manifest version: 0.3.0
anno <- CNV.create_anno(bin_minprobes = 10, bin_minsize = 100000, array_type = "EPIC",
+ chrXY = FALSE,
+ exclude_regions = NULL, detail_regions = NULL)
using genome annotations from UCSC
getting EPIC annotations
- 844316 probes used
creating bins
- 27074 bins created
merging bins
- 20394 bins remaining
anno
CNV annotation object
created : Wed Apr 07 19:21:27 2021
@genome : 22 chromosomes
@gap : 313 regions
@probes : 844316 probes
@exclude : 0 regions (overlapping 0 probes)
@detail : 0 regions (overlapping 0 probes)
@bins : 20394 bins (min/avg/max size: 100/131.2/5000kb, probes: 10/41.4/705)
minfi.data <- CNV.load(mset)
Warnmeldung:
In CNV.check(object) : intensities are abnormally low (< 5000).
minfi.controls <- pData(mset)$Status == "normal"
x <- CNV.fit(minfi.data["20D5108"], minfi.data[minfi.controls] , anno)
Fehler in .local(query, ref, anno, ...) :
query intensities not given for all probes.
sessionInfo( )
R version 4.0.2 (2020-06-22)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19042)
Matrix products: default
locale:
[1] LC_COLLATE=German_Austria.1252 LC_CTYPE=German_Austria.1252 LC_MONETARY=German_Austria.1252
[4] LC_NUMERIC=C LC_TIME=German_Austria.1252
attached base packages:
[1] stats4 parallel stats graphics grDevices utils datasets methods base
other attached packages:
[1] conumee_1.24.0 IlluminaHumanMethylationEPICanno.ilm10b2.hg19_0.6.0
[3] IlluminaHumanMethylation450kmanifest_0.4.0 IlluminaHumanMethylation450kanno.ilmn12.hg19_0.6.0
[5] IlluminaHumanMethylationEPICmanifest_0.3.0 IlluminaHumanMethylationEPICanno.ilm10b4.hg19_0.6.0
[7] minfi_1.36.0 bumphunter_1.32.0
[9] locfit_1.5-9.4 iterators_1.0.13
[11] foreach_1.5.1 Biostrings_2.58.0
[13] XVector_0.30.0 SummarizedExperiment_1.20.0
[15] Biobase_2.50.0 MatrixGenerics_1.2.0
[17] matrixStats_0.57.0 GenomicRanges_1.42.0
[19] GenomeInfoDb_1.26.2 IRanges_2.24.1
[21] S4Vectors_0.28.1 BiocGenerics_0.36.0
loaded via a namespace (and not attached):
[1] ellipsis_0.3.1 siggenes_1.64.0 mclust_5.4.7 DNAcopy_1.64.0
[5] base64_2.0 rstudioapi_0.13 bit64_4.0.5 AnnotationDbi_1.52.0
[9] fansi_0.4.2 xml2_1.3.2 codetools_0.2-16 splines_4.0.2
[13] sparseMatrixStats_1.2.0 cachem_1.0.1 scrime_1.3.5 Rsamtools_2.6.0
[17] annotate_1.68.0 dbplyr_2.1.0 HDF5Array_1.18.0 BiocManager_1.30.12
[21] readr_1.4.0 compiler_4.0.2 httr_1.4.2 assertthat_0.2.1
[25] Matrix_1.2-18 fastmap_1.1.0 limma_3.46.0 prettyunits_1.1.1
[29] tools_4.0.2 glue_1.4.2 GenomeInfoDbData_1.2.4 dplyr_1.0.3
[33] rappdirs_0.3.2 doRNG_1.8.2 Rcpp_1.0.6 vctrs_0.3.6
[37] rhdf5filters_1.2.0 multtest_2.46.0 preprocessCore_1.52.1 nlme_3.1-148
[41] rtracklayer_1.49.5 DelayedMatrixStats_1.12.3 stringr_1.4.0 lifecycle_1.0.0
[45] rngtools_1.5 XML_3.99-0.5 beanplot_1.2 zlibbioc_1.36.0
[49] MASS_7.3-51.6 hms_1.0.0 rhdf5_2.34.0 GEOquery_2.58.0
[53] RColorBrewer_1.1-2 curl_4.3 memoise_2.0.0 biomaRt_2.46.3
[57] reshape_0.8.8 stringi_1.5.3 RSQLite_2.2.3 genefilter_1.72.1
[61] GenomicFeatures_1.42.1 BiocParallel_1.24.1 rlang_0.4.10 pkgconfig_2.0.3
[65] bitops_1.0-6 nor1mix_1.3-0 lattice_0.20-41 purrr_0.3.4
[69] Rhdf5lib_1.12.1 GenomicAlignments_1.26.0 bit_4.0.4 tidyselect_1.1.0
[73] plyr_1.8.6 magrittr_2.0.1 R6_2.5.0 generics_0.1.0
[77] DelayedArray_0.16.1 DBI_1.1.1 pillar_1.5.1 survival_3.1-12
[81] RCurl_1.98-1.2 tibble_3.0.5 crayon_1.4.1 utf8_1.1.4
[85] BiocFileCache_1.14.0 progress_1.2.2 grid_4.0.2 data.table_1.13.6
[89] blob_1.2.1 digest_0.6.27 xtable_1.8-4 tidyr_1.1.2
[93] illuminaio_0.32.0 openssl_1.4.3 askpass_1.1 quadprog_1.5-8
thanks for reporting!
this error is probably caused by a few missing probes on newer EPIC arrays. after creating your anno object, could you try this line?
anno@probes <- anno@probes[names(anno@probes) %in% names(minfi::getLocations(IlluminaHumanMethylationEPICanno.ilm10b4.hg19::IlluminaHumanMethylationEPICanno.ilm10b4.hg19))]