MethylSet to MethyLumiSet
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Entering edit mode
Tom ▴ 10
@tom-10763
Last seen 23 months ago

Hi all,

I have several 450k and 850k (EPIC) array IDAT files. After combining them using minfi::combineArrays() and normalizing, I want to convert the object into MethyLumiSet class for downstream analysis.

Because no functions are implemented for that purpose, I tried to create a new MethyLumiSet inheriting the values from the combined MethylSet. However, I am not able to create a MethyLumiSet with some errors.

Is there a good way to achieve it?

> library(minfi)

> library(methylumi)

> illumina_epic=read.metharray.exp("~/My/EPICdata/directory/")
> illumina_450k=read.metharray.exp("~/My/450Kdata/directory/")
> comb=combineArrays(illumina_epic,illumina_450k,outType="IlluminaHumanMethylation450k")

> GRset.norm=preprocessNoob(comb, offset = 15, dyeCorr = TRUE, verbose = TRUE,dyeMethod="single")


> metLumi=new("MethyLumiSet",assayData=GRset.norm@assayData,phenoData=GRset.norm@phenoData,annotation=GRset.norm@annotation,betas=getBeta(GRset.norm))

Error in validObject(.Object) : 
  invalid class "MethyLumiSet" object: 'AssayData' missing 'betas'

 

I tried another way, which also ended with an error.

> x=new("MethyLumiSet")

> methylated(x) = getMeth(GRset.norm)

Error in .validate_assayDataElementReplace(obj, value) : 
  object and replacement value have different dimensions

 

> sessionInfo()
R version 3.3.2 (2016-10-31)
Platform: x86_64-apple-darwin13.4.0 (64-bit)
Running under: OS X Mavericks 10.9.5

locale:
[1] C

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

other attached packages:
[1] methylumi_2.20.0                        FDb.InfiniumMethylation.hg19_2.2.0    
[3] org.Hs.eg.db_3.4.0                      TxDb.Hsapiens.UCSC.hg19.knownGene_3.2.2
[5] GenomicFeatures_1.26.2                  AnnotationDbi_1.36.0                  
[7] matrixStats_0.51.0                      ggplot2_2.2.0                         
[9] reshape2_1.4.2                          scales_0.4.1                          
[11] minfi_1.20.2                            bumphunter_1.14.0                     
[13] locfit_1.5-9.1                          iterators_1.0.8                       
[15] foreach_1.4.3                           Biostrings_2.42.1                     
[17] XVector_0.14.0                          SummarizedExperiment_1.4.0            
[19] GenomicRanges_1.26.1                    GenomeInfoDb_1.10.1                   
[21] IRanges_2.8.1                           S4Vectors_0.12.1                      
[23] Biobase_2.34.0                          BiocGenerics_0.20.0                    

loaded via a namespace (and not attached):
[1] httr_1.2.1               nor1mix_1.2-2            splines_3.3.2          
[4] assertthat_0.1           doRNG_1.6                Rsamtools_1.26.1       
[7] RSQLite_1.1-1            lattice_0.20-34          limma_3.30.7           
[10] quadprog_1.5-5           digest_0.6.10            RColorBrewer_1.1-2     
[13] colorspace_1.3-2         preprocessCore_1.36.0    Matrix_1.2-7.1         
[16] plyr_1.8.4               GEOquery_2.40.0          siggenes_1.48.0        
[19] XML_3.98-1.5             biomaRt_2.30.0           genefilter_1.56.0      
[22] zlibbioc_1.20.0          xtable_1.8-2             BiocParallel_1.8.1     
[25] tibble_1.2               openssl_0.9.5            annotate_1.52.1        
[28] beanplot_1.2             pkgmaker_0.22            lazyeval_0.2.0         
[31] survival_2.40-1          magrittr_1.5             mclust_5.2             
[34] memoise_1.0.0            nlme_3.1-128             MASS_7.3-45            
[37] tools_3.3.2              registry_0.3             data.table_1.10.0      
[40] stringr_1.1.0            munsell_0.4.3            rngtools_1.2.4         
[43] base64_2.0               grid_3.3.2               RCurl_1.95-4.8         
[46] bitops_1.0-6             gtable_0.2.0             codetools_0.2-15       
[49] multtest_2.30.0          DBI_0.5-1                reshape_0.8.6          
[52] R6_2.2.0                 illuminaio_0.16.0        GenomicAlignments_1.10.0
[55] rtracklayer_1.34.1       stringi_1.1.2            Rcpp_0.12.8             

I would appreciate any helps or comments.

Tom

 

 

minfi methylumi watermelon • 911 views
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Entering edit mode
> library(watermelon)

> x=as.methylumi(GRset.norm)

also ended with the same error.

Error in .validate_assayDataElementReplace(obj, value) : 
  object and replacement value have different dimensions

Any suggestion would be very welcome.

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