Copy number Variation analysis using conumee
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shweta • 0
@shweta-24797
Last seen 3.0 years ago

Dear All,

I would like to perform copy number variation analysis using conumee package in R, mainly to get the copy number plots. I had a few questions with respect to that and I hope to get some help.

  1. In the conumee vignette, while annotating there is exclude region and detail region data in it, I wonder if there is any specific dataset for it? For eg for brain cancers some common regions which need to be excluded? OR, I could make a data of all the probes that were excluded from my analysis (such as poor quality probes, cross-reactive probes and those with SNPs) in minfi and then include it in the exclude regions for annotation in conumee? Will this be the right thing to do?

  2. I do not have any control sample files, I obtained some control .IDAT files from two GEO sets for EPIC arrays as mentioned here and tried to process just one sample initially, but my query dataset has more probes than my annotation dataset and I get an error which says

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

I checked for a solution here using subsetByOverlaps() but my query object has more probes than annotations so I am not sure if that is causing the trouble.

I would really appreciate it if anyone could help me with this as I am processing all this for the first time.

Thank you very much in advance,

Shweta

sessionInfo()
R version 4.0.2 (2020-06-22)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19041)

Matrix products: default

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

other attached packages:
 [1] CopyNeutralIMA_1.6.0                               
 [2] pheatmap_1.0.12                                    
 [3] ComplexHeatmap_2.4.3                               
 [4] ggplot2_3.3.3                                      
 [5] reshape2_1.4.4                                     
 [6] dplyr_1.0.4                                        
 [7] illuminaio_0.30.0                                  
 [8] methylationArrayAnalysis_1.12.0                    
 [9] FlowSorted.Blood.450k_1.26.0                       
[10] stringr_1.4.0                                      
[11] DMRcate_2.2.3                                      
[12] Gviz_1.32.0                                        
[13] minfiData_0.34.0                                   
[14] missMethyl_1.22.0                                  
[15] IlluminaHumanMethylationEPICanno.ilm10b4.hg19_0.6.0
[16] RColorBrewer_1.1-2                                 
[17] limma_3.44.3                                       
[18] BiocStyle_2.16.1                                   
[19] rmarkdown_2.6                                      
[20] knitr_1.31                                         
[21] conumee_1.22.0                                     
[22] IlluminaHumanMethylationEPICmanifest_0.3.0         
[23] IlluminaHumanMethylationEPICanno.ilm10b2.hg19_0.6.0
[24] IlluminaHumanMethylation450kmanifest_0.4.0         
[25] IlluminaHumanMethylation450kanno.ilmn12.hg19_0.6.0 
[26] minfi_1.34.0                                       
[27] bumphunter_1.30.0                                  
[28] locfit_1.5-9.4                                     
[29] iterators_1.0.13                                   
[30] foreach_1.5.1                                      
[31] Biostrings_2.56.0                                  
[32] XVector_0.28.0                                     
[33] SummarizedExperiment_1.18.2                        
[34] DelayedArray_0.14.1                                
[35] matrixStats_0.58.0                                 
[36] Biobase_2.48.0                                     
[37] GenomicRanges_1.40.0                               
[38] GenomeInfoDb_1.24.2                                
[39] IRanges_2.22.2                                     
[40] S4Vectors_0.26.1                                   
[41] BiocGenerics_0.34.0                                

loaded via a namespace (and not attached):
  [1] utf8_1.1.4                    R.utils_2.10.1                tidyselect_1.1.0             
  [4] RSQLite_2.2.3                 AnnotationDbi_1.50.3          htmlwidgets_1.5.3            
  [7] BiocParallel_1.22.0           munsell_0.5.0                 codetools_0.2-18             
 [10] preprocessCore_1.50.0         statmod_1.4.35                withr_2.4.1                  
 [13] colorspace_2.0-0              rstudioapi_0.13               Rdpack_2.1.1                 
 [16] GenomeInfoDbData_1.2.3        bit64_4.0.5                   rhdf5_2.32.4                 
 [19] vctrs_0.3.6                   generics_0.1.0                xfun_0.20                    
 [22] biovizBase_1.36.0             BiocFileCache_1.12.1          R6_2.5.0                     
 [25] clue_0.3-58                   AnnotationFilter_1.12.0       bitops_1.0-6                 
 [28] cachem_1.0.3                  reshape_0.8.8                 assertthat_0.2.1             
 [31] promises_1.1.1                scales_1.1.1                  bsseq_1.24.4                 
 [34] nnet_7.3-15                   gtable_0.3.0                  ensembldb_2.12.1             
 [37] rlang_0.4.10                  genefilter_1.70.0             GlobalOptions_0.1.2          
 [40] splines_4.0.2                 rtracklayer_1.48.0            lazyeval_0.2.2               
 [43] DSS_2.36.0                    GEOquery_2.56.0               dichromat_2.0-0              
 [46] checkmate_2.0.0               BiocManager_1.30.10           yaml_2.2.1                   
 [49] GenomicFeatures_1.40.1        backports_1.2.1               httpuv_1.5.5                 
 [52] Hmisc_4.4-2                   tools_4.0.2                   nor1mix_1.3-0                
 [55] ellipsis_0.3.1                DNAcopy_1.62.0                siggenes_1.62.0              
 [58] Rcpp_1.0.6                    plyr_1.8.6                    base64enc_0.1-3              
 [61] progress_1.2.2                zlibbioc_1.34.0               purrr_0.3.4                  
 [64] RCurl_1.98-1.2                prettyunits_1.1.1             rpart_4.1-15                 
 [67] openssl_1.4.3                 GetoptLong_1.0.5              cluster_2.1.1                
 [70] tinytex_0.30                  magrittr_2.0.1                data.table_1.13.6            
 [73] circlize_0.4.12               ProtGenerics_1.20.0           mime_0.9                     
 [76] hms_1.0.0                     evaluate_0.14                 xtable_1.8-4                 
 [79] XML_3.99-0.5                  jpeg_0.1-8.1                  mclust_5.4.7                 
 [82] shape_1.4.5                   gridExtra_2.3                 compiler_4.0.2               
 [85] biomaRt_2.44.4                tibble_3.0.6                  crayon_1.4.1                 
 [88] R.oo_1.24.0                   htmltools_0.5.1.1             later_1.1.0.1                
 [91] Formula_1.2-4                 tidyr_1.1.2                   DBI_1.1.1                    
 [94] ExperimentHub_1.14.2          dbplyr_2.1.0                  MASS_7.3-53                  
 [97] rappdirs_0.3.3                Matrix_1.2-18                 readr_1.4.0                  
[100] permute_0.9-5                 rbibutils_2.0                 quadprog_1.5-8               
[103] R.methodsS3_1.8.1             pkgconfig_2.0.3               GenomicAlignments_1.24.0     
[106] foreign_0.8-81                xml2_1.3.2                    annotate_1.66.0              
[109] rngtools_1.5                  multtest_2.44.0               beanplot_1.2                 
[112] doRNG_1.8.2                   scrime_1.3.5                  VariantAnnotation_1.34.0     
[115] digest_0.6.27                 base64_2.0                    htmlTable_2.1.0              
[118] edgeR_3.30.3                  DelayedMatrixStats_1.10.1     curl_4.3                     
[121] shiny_1.6.0                   Rsamtools_2.4.0               gtools_3.8.2                 
[124] rjson_0.2.20                  lifecycle_1.0.0               nlme_3.1-152                 
[127] Rhdf5lib_1.10.1               askpass_1.1                   BSgenome_1.56.0              
[130] fansi_0.4.2                   pillar_1.5.1                  lattice_0.20-41              
[133] fastmap_1.1.0                 httr_1.4.2                    survival_3.2-7               
[136] interactiveDisplayBase_1.26.3 glue_1.4.2                    png_0.1-7                    
[139] BiocVersion_3.11.1            bit_4.0.4                     stringi_1.5.3                
[142] HDF5Array_1.16.1              blob_1.2.1                    org.Hs.eg.db_3.11.4          
[145] AnnotationHub_2.20.2          latticeExtra_0.6-29           memoise_2.0.0
CopyNumberVariation CopyNumberPlots • 871 views
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