After subsetMaf, error in oncoplot about maftools

[PoisonAlien]

Hi,
can you attach your maf file if possible (after subsetting)? How many samples do you have after subsetting? and what version of ComplexHeatmap are you using (ComplexHeatmap, which is used to plot oncoplot has been updated recently, I have fixed issues to support newer version of ComplexHeatmap) ?

[hmkim]

merged.maf.gz

I subsetting with gene list.

target_gene_list = c('APITD1-CORT', 'APITD1', 'PRDM2', 'ARID1A', 'NFYC', 'JAK1', 'RBM15', 'DENND2D', 'PDE4DIP', 'FCGR3A', 'IGKV1D-8', 'CCDC66', 'ZNF518B', 'SGCB', 'NAF1', 'DDX60L', 'ERBB2IP', 'ERAP2', 'CTNNA1', 'BTN3A2', 'EEF1A1', 'AIM1', 'ZNF92', 'C7orf43', 'KMT2C', 'RSPO2', 'TRAPPC9', 'FAM83H', 'NPR2', 'PHF2', 'HIATL1', 'C9orf156', 'FAM208B', 'MGEA5', 'PHRF1', 'MUC6', 'CTR9', 'IGHMBP2', 'ANKRD42', 'RAD52', 'FOXM1', 'APOBEC1', 'IPO8', 'GXYLT1', 'KMT2D', 'ACVR1B', 'WIBG', 'CEP290', 'CDK17', 'TCP11L2', 'CRY1', 'PWP1', 'TGDS', 'FBXO33', 'KLHL28', 'ELMSAN1', 'GTF2A1', 'CDC42BPB', 'IGHV3-21', 'ITPKA', 'IREB2', 'GOLGA6L4', 'MEF2A', 'ZNF646', 'CKLF', 'ZNF19', 'GINS2', 'YWHAE', 'DERL2', 'TP53', 'RNF43', 'HEATR6', 'PSMC5', 'P4HB', 'CYB5A', 'GADD45B', 'DENND1C', 'DNM2', 'CEBPG', 'ZNF420', 'KDELR1', 'ZNF160', 'CPXM1', 'SLC35C2', 'B4GALT5', 'NDUFV3', 'C21orf67', 'C21orf58', 'IGLVI-70', 'IGLV8-61', 'ZNRF3', 'MORC2', 'KDELR3', 'ZFX', 'NKRF')

and I use the ComplexHeatmap_1.10.2.

> require(maftools)
필요한 패키지를 로딩중입니다: maftools
> sessionInfo()
R version 3.3.1 (2016-06-21)
Platform: x86_64-apple-darwin13.4.0 (64-bit)
Running under: OS X 10.11.6 (El Capitan)

locale:
[1] ko_KR.UTF-8/ko_KR.UTF-8/ko_KR.UTF-8/C/ko_KR.UTF-8/ko_KR.UTF-8

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

other attached packages:
[1] maftools_0.99.40    Biobase_2.32.0      BiocGenerics_0.18.0

loaded via a namespace (and not attached):
  [1] nlme_3.1-128               bitops_1.0-6               doParallel_1.0.10         
  [4] RColorBrewer_1.1-2         prabclus_2.2-6             GenomeInfoDb_1.8.3        
  [7] tools_3.3.1                R6_2.1.2                   KernSmooth_2.23-15        
 [10] DBI_0.5                    colorspace_1.2-6           trimcluster_0.1-2         
 [13] nnet_7.3-12                GetoptLong_0.1.4           chron_2.3-47              
 [16] pkgmaker_0.22              slam_0.1-37                rtracklayer_1.32.2        
 [19] caTools_1.17.1             diptest_0.75-7             scales_0.4.0              
 [22] DEoptimR_1.0-6             mvtnorm_1.0-5              robustbase_0.92-6         
 [25] NMF_0.20.6                 stringr_1.0.0              digest_0.6.10             
 [28] Rsamtools_1.24.0           rmarkdown_1.0              cometExactTest_0.1.3      
 [31] XVector_0.12.1             htmltools_0.3.5            changepoint_2.2.1         
 [34] BSgenome_1.40.1            GlobalOptions_0.0.10       RSQLite_1.0.0             
 [37] shape_1.4.2                zoo_1.7-13                 mclust_5.2                
 [40] BiocParallel_1.6.6         DPpackage_1.1-6            gtools_3.5.0              
 [43] dendextend_1.2.0           dplyr_0.5.0                VariantAnnotation_1.18.7  
 [46] RCurl_1.95-4.8             magrittr_1.5               modeltools_0.2-21         
 [49] wordcloud_2.5              Matrix_1.2-6               Rcpp_0.12.6               
 [52] munsell_0.4.3              S4Vectors_0.10.3           stringi_1.1.1             
 [55] whisker_0.3-2              yaml_2.1.13                MASS_7.3-45               
 [58] SummarizedExperiment_1.2.3 zlibbioc_1.18.0            flexmix_2.3-13            
 [61] gplots_3.0.1               plyr_1.8.4                 grid_3.3.1                
 [64] gdata_2.17.0               ggrepel_0.5                lattice_0.20-33           
 [67] Biostrings_2.40.2          cowplot_0.6.2              splines_3.3.1             
 [70] GenomicFeatures_1.24.5     circlize_0.3.8             knitr_1.14                
 [73] ComplexHeatmap_1.10.2      GenomicRanges_1.24.2       rjson_0.2.15              
 [76] fpc_2.1-10                 rngtools_1.2.4             reshape2_1.4.1            
 [79] codetools_0.2-14           biomaRt_2.28.0             stats4_3.3.1              
 [82] XML_3.98-1.4               evaluate_0.9               data.table_1.9.6          
 [85] foreach_1.4.3              gtable_0.2.0               kernlab_0.9-24            
 [88] assertthat_0.1             ggplot2_2.1.0              gridBase_0.4-7            
 [91] xtable_1.8-2               class_7.3-14               survival_2.39-5           
 [94] tibble_1.1                 iterators_1.0.8            GenomicAlignments_1.8.4   
 [97] AnnotationDbi_1.34.4       registry_0.3               IRanges_2.6.1             
[100] cluster_2.0.4             

[PoisonAlien]

Hi, thanks for the file. It seems to be problem during plotting rowbars. I am looking into it.
Meanwhile, if you're okay with it, you can generate plot with drawRowBar = FALSE
I will get back to it soon!

[hmkim]

@PoisonAlien Thanks, and I wonder how can I find the filtered sample

> laml
An object of class  MAF 
                        ID summary         Mean Median
 1:             NCBI_Build  GRCh37           NA     NA
 2:                 Center       .           NA     NA
 3:                Samples      34           NA     NA
 4:                 nGenes    2720           NA     NA
 5:      Missense_Mutation    5783 170.08823529  130.0
 6:      Nonsense_Mutation     131   3.85294118    1.5
 7:       Nonstop_Mutation       2   0.05882353    0.0
 8:            Splice_Site      31   0.91176471    1.0
 9: Translation_Start_Site      14   0.41176471    0.0
10:                  total    5961 175.32352941  133.5
> laml = subsetMaf(maf = laml, genes = target_gene_list, mafObj = TRUE)
Creating oncomatrix (this might take a while)..
Sorting..
> laml
An object of class  MAF 
                        ID summary        Mean Median
 1:             NCBI_Build  GRCh37          NA     NA
 2:                 Center       .          NA     NA
 3:                Samples      33          NA     NA
 4:                 nGenes     180          NA     NA
 5:      Missense_Mutation     268  8.12121212      6
 6:      Nonsense_Mutation      83  2.51515152      1
 7:       Nonstop_Mutation       2  0.06060606      0
 8:            Splice_Site       9  0.27272727      0
 9: Translation_Start_Site       7  0.21212121      0
10:                  total     369 11.18181818      6
> ?subsetMaf

After subsetting, 1 sample is out.
Why and How can I figure out the sample ?

[PoisonAlien]

Hi, try this:

#for sample info
getSampleSummary(x = laml)
getSampleSummary(x = laml.subset)
#for gene info
getGeneSummary(x = laml) 
getGeneSummary(x = laml.subset)

[PoisonAlien]

Hi,
I have fixed it. Can you try again (from github) and let me know ?