Question

conumee error: query intensities not given for all probes.

1

Entering edit mode

yura.grabovska ▴ 30

@yuragrabovska-9835

Last seen 3.1 years ago

United Kingdom

Conumee error:

Error in .local(query, ref, anno, ...) : 
  query intensities not given for all probes.

This error results when I use

x <- CNV.fit(data[1], controls.data, anno)

The data object was generated by:

rgSet <- combineArrays(rgSet.450k, rgSet.850k)
mSet <- preprocessNoob(rgSet, dyeMethod = "single")
data <- CNV.load(mSet)

The anno object was made by:

anno <- CNV.create_anno(chrXY = TRUE, 
                        exclude_regions = exclude_regions, 
                        detail_regions = detail_regions,
                        array_type = "overlap")

Controls data is generated in a similar way to the test data.

Could you please let me what checks to carry out? I current work around this by amending the anno data to reflect the missing problems and end up dropping quite a number of probes in the process.

Many thanks

R version 3.4.0 (2017-04-21)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 16.04.2 LTS

Matrix products: default
BLAS: /usr/lib/libblas/libblas.so.3.6.0
LAPACK: /usr/lib/lapack/liblapack.so.3.6.0

locale:
 [1] LC_CTYPE=en_GB.UTF-8       LC_NUMERIC=C               LC_TIME=en_GB.UTF-8        LC_COLLATE=en_GB.UTF-8     LC_MONETARY=en_GB.UTF-8   
 [6] LC_MESSAGES=en_GB.UTF-8    LC_PAPER=en_GB.UTF-8       LC_NAME=C                  LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_GB.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] stats4    parallel  stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] conumee_1.10.0                                      IlluminaHumanMethylationEPICmanifest_0.3.0          IlluminaHumanMethylationEPICanno.ilm10b2.hg19_0.6.0
 [4] IlluminaHumanMethylation450kmanifest_0.4.0          IlluminaHumanMethylation450kanno.ilmn12.hg19_0.6.0  minfi_1.22.1                                       
 [7] bumphunter_1.16.0                                   locfit_1.5-9.1                                      iterators_1.0.8                                    
[10] foreach_1.4.3                                       Biostrings_2.44.1                                   XVector_0.16.0                                     
[13] SummarizedExperiment_1.6.3                          DelayedArray_0.2.7                                  matrixStats_0.52.2                                 
[16] Biobase_2.36.2                                      GenomicRanges_1.28.3                                GenomeInfoDb_1.12.2                                
[19] IRanges_2.10.2                                      S4Vectors_0.14.3                                    BiocGenerics_0.22.0                                

loaded via a namespace (and not attached):
 [1] httr_1.2.1               nor1mix_1.2-2            bit64_0.9-7              splines_3.4.0            doRNG_1.6.6              blob_1.1.0              
 [7] GenomeInfoDbData_0.99.0  Rsamtools_1.28.0         RSQLite_2.0              lattice_0.20-35          limma_3.32.2             quadprog_1.5-5          
[13] digest_0.6.12            RColorBrewer_1.1-2       preprocessCore_1.38.1    Matrix_1.2-10            plyr_1.8.4               GEOquery_2.42.0         
[19] siggenes_1.50.0          XML_3.98-1.9             biomaRt_2.32.1           genefilter_1.58.1        zlibbioc_1.22.0          xtable_1.8-2            
[25] BiocParallel_1.10.1      tibble_1.3.3             openssl_0.9.6            annotate_1.54.0          beanplot_1.2             pkgmaker_0.22           
[31] GenomicFeatures_1.28.4   survival_2.41-3          magrittr_1.5             mclust_5.3               memoise_1.1.0            nlme_3.1-131            
[37] MASS_7.3-47              tools_3.4.0              registry_0.3             data.table_1.10.4        stringr_1.2.0            rngtools_1.2.4          
[43] AnnotationDbi_1.38.1     base64_2.0               compiler_3.4.0           rlang_0.1.1              grid_3.4.0               RCurl_1.95-4.8          
[49] bitops_1.0-6             DNAcopy_1.50.1           codetools_0.2-15         multtest_2.32.0          DBI_0.7                  reshape_0.8.6           
[55] R6_2.2.2                 illuminaio_0.18.0        GenomicAlignments_1.12.1 rtracklayer_1.36.3       bit_1.1-12               stringi_1.1.5           
[61] Rcpp_0.12.11

conumee • 4.5k views

ADD COMMENT • link updated 11 months ago by Mingkee • 0 • written 7.4 years ago by yura.grabovska ▴ 30

5

Entering edit mode

SplittingInfinity ▴ 60

@splittinginfinity-11669

Last seen 3.6 years ago

Canada

I had the same problem as well. In case this may be interesting to others, the temporary measure that I'm doing is finding the overlaps between sample and anno file right after CNV.load:

data <- CNV.load(Mset)

controls.data <- CNV.load(MsetControls)

### find overlaps ###

Mset <- mapToGenome(Mset)

anno@probes <- subsetByOverlaps(anno@probes, granges(Mset))

ADD COMMENT • link 7.4 years ago SplittingInfinity ▴ 60

0

Entering edit mode

Unfortunately I experience the same problem when combining 450K and EPIC arrays. Could you please elaborate on your solution, I'm not sure I understand what you are doing in this part?

### find overlaps ###

Mset <- mapToGenome(Mset)

anno@probes <- subsetByOverlaps(anno@probes, granges(Mset))

Many thanks

ADD REPLY • link 4.2 years ago MoltenLight ▴ 10

0

Entering edit mode

Hey, were you able to fix this issue? :)

Shweta

ADD REPLY • link 3.8 years ago shweta • 0

0

Entering edit mode

Yes, thanks :) I actually don't remember exactly what I've done, but I found a workaround!

ADD REPLY • link 3.8 years ago MoltenLight ▴ 10

0

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glad you got it to work. this would be my solution:

when combining 450k and EPIC datasets, make sure to use CNV.create_anno() with array_type="overlap"

then use this line (similar to the above):

anno@probes <- anno@probes[names(anno@probes) %in% names(minfi::getLocations(IlluminaHumanMethylationEPICanno.ilm10b4.hg19::IlluminaHumanMethylationEPICanno.ilm10b4.hg19))]

as always, the larger and more diverse (450k/EPIC, good/bad quality ..) the reference set, the better the results.

ADD REPLY • link 3.6 years ago volker hovestadt ▴ 40

0

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Hi, I followed your suggestion with CNV.create_anno() with array_type="overlap" and IlluminaHumanMethylationEPICanno.ilm10b4.hg19 but I still. get the same error. Could you please help me fix this issue? For minfi.data, it works fine.

ADD REPLY • link 11 months ago Mingkee • 0

score 4 · Accepted Answer · 2017-07-11

4

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volker hovestadt ▴ 40

@volker-hovestadt-7393

Last seen 3.6 years ago

boston

there are some probes missing on more recent EPIC arrays which causes this error.

for now you can try installing the more recent "IlluminaHumanMethylationEPICanno.ilm10b3.hg19" package and adapt the "CNV.create_anno" function (line 96: https://github.com/Bioconductor-mirror/conumee/blob/release-3.5/R/annotation.R).

i will fix this in the next release. thank you for reporting this bug.

ADD COMMENT • link 7.4 years ago volker hovestadt ▴ 40

0

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Thank you for getting back to me. We assumed there was something going on along these lines as I recently had a similar problem with minfi reading in newer EPIC array idats before the update dropped.

Will implement change you recommended.

ADD REPLY • link 7.4 years ago yura.grabovska ▴ 30