Entering edit mode
Hello
I am trying to use the TCGAbiolinks package to extract mutation data for several types of tumors I am interested in.
I am using GDCquery_Maf, using exactly the syntax indicated in the help file:
acc.maf <- GDCquery_Maf("ACC")
However I then get the error:
Error in missing(tumor) : 'missing' can only be used for arguments
The maf file is actually written in my working directory, but for some reason is not imported into the R workspace. Also when I'm using save.csv=TRUE, no csv file is created.
I have tried this with several tumor types, and always got the same error.
Any idea what may be causing this?
Thanks in advacne
Dolev Rahat
> sessionInfo() R version 3.3.2 (2016-10-31) Platform: x86_64-pc-linux-gnu (64-bit) Running under: Ubuntu 14.04.5 LTS locale: [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=en_US.UTF-8 [4] LC_COLLATE=en_US.UTF-8 LC_MONETARY=he_IL.UTF-8 LC_MESSAGES=en_US.UTF-8 [7] LC_PAPER=he_IL.UTF-8 LC_NAME=C LC_ADDRESS=C [10] LC_TELEPHONE=C LC_MEASUREMENT=he_IL.UTF-8 LC_IDENTIFICATION=C attached base packages: [1] stats graphics grDevices utils datasets methods base other attached packages: [1] TCGA2STAT_1.2 BiocInstaller_1.22.3 TCGAbiolinks_2.0.13 curl_2.3 loaded via a namespace (and not attached): [1] TH.data_1.0-8 colorspace_1.3-2 [3] rjson_0.2.15 hwriter_1.3.2 [5] class_7.3-14 modeltools_0.2-21 [7] mclust_5.2.2 circlize_0.3.9 [9] XVector_0.12.1 GenomicRanges_1.24.3 [11] GlobalOptions_0.0.10 parmigene_1.0.2 [13] matlab_1.0.2 hexbin_1.27.1 [15] affyio_1.42.0 ggrepel_0.6.5 [17] flexmix_2.3-13 AnnotationDbi_1.34.4 [19] mvtnorm_1.0-5 xml2_1.1.1 [21] coin_1.1-3 codetools_0.2-15 [23] splines_3.3.2 R.methodsS3_1.7.1 [25] doParallel_1.0.10 DESeq_1.24.0 [27] robustbase_0.92-7 knitr_1.15.2 [29] geneplotter_1.50.0 jsonlite_1.2 [31] Rsamtools_1.24.0 annotate_1.50.1 [33] cluster_2.0.5 kernlab_0.9-25 [35] R.oo_1.21.0 supraHex_1.10.0 [37] graph_1.50.0 readr_1.0.0 [39] httr_1.2.1 assertthat_0.1 [41] Matrix_1.2-8 lazyeval_0.2.0 [43] TxDb.Hsapiens.UCSC.hg19.knownGene_3.2.2 limma_3.28.21 [45] tools_3.3.2 igraph_1.0.1 [47] gtable_0.2.0 affy_1.50.0 [49] dplyr_0.5.0 ggthemes_3.3.0 [51] ShortRead_1.30.0 Rcpp_0.12.9 [53] Biobase_2.32.0 trimcluster_0.1-2 [55] Biostrings_2.40.2 gdata_2.17.0 [57] ape_4.1 preprocessCore_1.34.0 [59] nlme_3.1-131 rtracklayer_1.32.2 [61] iterators_1.0.8 fpc_2.1-10 [63] stringr_1.2.0 rvest_0.3.2 [65] gtools_3.5.0 XML_3.98-1.5 [67] dendextend_1.4.0 edgeR_3.14.0 [69] DEoptimR_1.0-8 zlibbioc_1.18.0 [71] MASS_7.3-45 zoo_1.7-14 [73] scales_0.4.1 aroma.light_3.2.0 [75] parallel_3.3.2 SummarizedExperiment_1.2.3 [77] sandwich_2.3-4 RColorBrewer_1.1-2 [79] ComplexHeatmap_1.13.1 memoise_1.0.0 [81] gridExtra_2.2.1 ggplot2_2.2.1 [83] downloader_0.4 biomaRt_2.28.0 [85] reshape_0.8.6 latticeExtra_0.6-28 [87] stringi_1.1.2 RSQLite_1.1-2 [89] highr_0.6 genefilter_1.54.2 [91] S4Vectors_0.10.3 foreach_1.4.3 [93] caTools_1.17.1 GenomicFeatures_1.24.5 [95] BiocGenerics_0.18.0 BiocParallel_1.6.6 [97] shape_1.4.2 GenomeInfoDb_1.8.7 [99] prabclus_2.2-6 matrixStats_0.51.0 [101] bitops_1.0-6 dnet_1.0.10 [103] lattice_0.20-34 GenomicAlignments_1.8.4 [105] GGally_1.3.0 plyr_1.8.4 [107] magrittr_1.5 R6_2.2.0 [109] gplots_3.0.1 IRanges_2.6.1 [111] multcomp_1.4-6 DBI_0.5-1 [113] whisker_0.3-2 survival_2.40-1 [115] RCurl_1.95-4.8 nnet_7.3-12 [117] tibble_1.2 EDASeq_2.6.2 [119] KernSmooth_2.23-15 viridis_0.3.4 [121] GetoptLong_0.1.5 grid_3.3.2 [123] data.table_1.10.4 Rgraphviz_2.16.0 [125] ConsensusClusterPlus_1.36.0 digest_0.6.12 [127] diptest_0.75-7 xtable_1.8-2 [129] R.utils_2.5.0 stats4_3.3.2 [131] munsell_0.4.3
