conumee (for EPIC): query intensities not given for all probes
Entering edit mode
Last seen 10 weeks ago

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!

class: MethylSet 
dim: 866238 8 
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
  array: IlluminaHumanMethylationEPIC
  annotation: ilm10b4.hg19
  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
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) <- CNV.load(mset)
In CNV.check(object) : intensities are abnormally low (< 5000).

minfi.controls <- pData(mset)$Status == "normal" 

x <-["20D5108"],[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

[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  
IlluminaHumanMethylationEPICmanifest minfi conumee • 137 views
Entering edit mode

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))]


Login before adding your answer.

Traffic: 452 users visited in the last hour
Help About
Access RSS

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.

Powered by the version 2.3.6