Question: minfi MethylationEPIC errors
0
gravatar for ceciliebucher
2.4 years ago by
ceciliebucher0 wrote:

I am new to analyzing array data and I am currently trying to analyze some 850k array data using minfi. I have loaded the IlluminaHumanMethylationEPICmanifest and IlluminaHumanMethylationEPICanno.ilm10b2.hg19. I am following this "recipe": A cross-package Bioconductor workflow for analysing methylation array data. The read.metharray.exp() function works (and everything else down to the point of normalisation) and i manage to assign the right annotation. However, many downstream functions like qcReport(), preprocessQuantile(), preprocessNoob(), preprocessFunnorm() give me an error:

[preprocessQuantile] Mapping to genome.
Error in `assayDataElement<-`(`*tmp*`, "Meth", validate = FALSE, value = c(471,  :
  unused argument (validate = FALSE)
In addition: Warning message:
display list redraw incomplete 

I cannot seem to figure out what the problem is, i have also tried to use the 450k annotation as well but it still does not work. 

ADD COMMENTlink modified 2.4 years ago • written 2.4 years ago by ceciliebucher0
> sessionInfo()
R version 3.3.3 (2017-03-06)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Debian GNU/Linux 8 (jessie)

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

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

other attached packages:
 [1] IlluminaHumanMethylation450kanno.ilmn12.hg19_0.6.0  
stringr_1.2.0   
DMRcate_1.10.8 
 [4] DMRcatedata_1.10.1  
DSS_2.14.0
bsseq_1.10.0
 [7] Gviz_1.18.2
missMethyl_1.8.0
RColorBrewer_1.1-2
[10] limma_3.30.13 
genefilter_1.48.1                                   
annotate_1.44.0                                    
[13] XML_3.98-1.5                                        
AnnotationDbi_1.36.2                                
shinyMethyl_1.10.0                                 
[16] IlluminaHumanMethylation450kmanifest_0.4.0          
shiny_1.0.0                                         
FlowSorted.Blood.450k_1.12.0                       
[19] mclust_5.2.2                                        
zlibbioc_1.12.0                                     
matrixStats_0.51.0                                 
[22] IlluminaHumanMethylationEPICanno.ilm10b2.hg19_0.6.0 IlluminaHumanMethylationEPICmanifest_0.3.0
BiocInstaller_1.24.0                               
[25] minfi_1.20.2
bumphunter_1.14.0
locfit_1.5-9.1            
[28] iterators_1.0.8
foreach_1.4.3
Biostrings_2.42.1                                  
[31] XVector_0.14.0
SummarizedExperiment_1.4.0
GenomicRanges_1.26.3                               
[34] GenomeInfoDb_1.10.3
IRanges_2.8.1
S4Vectors_0.12.1                                   
[37] Biobase_2.26.0
BiocGenerics_0.20.0                                

loaded via a namespace (and not attached):
 [1] colorspace_1.3-2              siggenes_1.48.0               biovizBase_1.22.0             htmlTable_1.9                 base64enc_0.1-3               dichromat_2.0-0              
 [7] base64_2.0                    interactiveDisplayBase_1.12.0 R.methodsS3_1.7.1             codetools_0.2-15              methylumi_2.20.0              knitr_1.15.1                 
[13] Formula_1.2-1                 Rsamtools_1.26.1              cluster_2.0.5                 GO.db_3.4.0                   R.oo_1.21.0                   httr_1.2.1                   
[19] backports_1.0.5               assertthat_0.1                Matrix_1.2-7.1                lazyeval_0.2.0                acepack_1.4.1                 htmltools_0.3.5              
[25] tools_3.3.3                   gtable_0.2.0                  doRNG_1.6                     Rcpp_0.12.9                   multtest_2.30.0               preprocessCore_1.36.0        
[31] nlme_3.1-128                  rtracklayer_1.34.2            mime_0.5                      ensembldb_1.6.2               gtools_3.5.0                  rngtools_1.2.4               
[37] statmod_1.4.29                beanplot_1.2                  org.Hs.eg.db_3.4.0            AnnotationHub_2.6.4           MASS_7.3-45                   scales_0.4.1                 
[43] BSgenome_1.42.0               VariantAnnotation_1.20.2      GEOquery_2.40.0               yaml_2.1.14                   memoise_1.0.0                 gridExtra_2.2.1              
[49] ggplot2_2.2.1                 pkgmaker_0.22                 biomaRt_2.30.0                rpart_4.1-10                  reshape_0.8.6                 latticeExtra_0.6-28          
[55] stringi_1.1.2                 RSQLite_1.1-2                 permute_0.9-4                 checkmate_1.8.2               GenomicFeatures_1.26.3        BiocParallel_1.8.1           
[61] bitops_1.0-6                  nor1mix_1.2-2                 lattice_0.20-34               ruv_0.9.6                     GenomicAlignments_1.10.0      htmlwidgets_0.8              
[67] plyr_1.8.4                    magrittr_1.5                  R6_2.2.0                      Hmisc_4.0-2                   DBI_0.6                       foreign_0.8-67               
[73] survival_2.40-1               RCurl_1.95-4.8                nnet_7.3-12                   tibble_1.2                    data.table_1.10.4             digest_0.6.12                
[79] xtable_1.8-2                  httpuv_1.3.3                  R.utils_2.5.0                 illuminaio_0.16.0             openssl_0.9.6                 munsell_0.4.3                
[85] registry_0.3                  BiasedUrn_1.07                quadprog_1.5-5 
ADD REPLYlink written 2.4 years ago by ceciliebucher0

It would also be helpful if you would show the code you used up to that point.

ADD REPLYlink written 2.4 years ago by James W. MacDonald50k
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