MethylSet to MethyLumiSet
0
0
Entering edit mode
Tom ▴ 10
@tom-10763
Last seen 4.7 years 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 • 1.5k views
ADD COMMENT
0
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.

ADD REPLY

Login before adding your answer.

Traffic: 490 users visited in the last hour
Help About
FAQ
Access RSS
API
Stats

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

Powered by the version 2.3.6