I try to use TCGAbiolinks in Rstudio(GDCquery function), but it always has a error : cannot open file '~/R/x86_64-pc-linux-gnu-library/3.3/readr/R/sysdata.rdb': No such file or directory. I have try these on Windows and Ubnutu, but the result is the same. I am sure this package exist in right posistion. I am not sure whether this problem is caused by the permission. I tried to reinstall readr, but I still has this problem. However, i try to use TCGAbiolinks through command line, it seems work. Does TCGAbiolinks support Rstudo or it need some special set?

  library("TCGAbiolinks", lib.loc="~/R/x86_64-pc-linux-gnu-library/3.3")
     query <- GDCquery(project = "TARGET-AML",
                       data.category = "Transcriptome Profiling",
                       data.type = "Gene Expression Quantification", 
                       workflow.type = "HTSeq - Counts")

    error message: cannot open file '~/R/x86_64-pc-linux-gnu-library/3.3/readr/R/sysdata.rdb': No such file or directory.

Here is my sessioninfo:

R version 3.3.1 (2016-06-21)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 16.04.1 LTS

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C               LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8    LC_PAPER=en_US.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C             LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

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

other attached packages:
[1] TCGAbiolinks_2.0.6

loaded via a namespace (and not attached):
  [1] circlize_0.3.8                          aroma.light_3.2.0                       plyr_1.8.4                             
  [4] igraph_1.0.1                            lazyeval_0.2.0                          ConsensusClusterPlus_1.36.0            
  [7] splines_3.3.1                           BiocParallel_1.6.6                      GenomeInfoDb_1.8.3                     
 [10] ggplot2_2.1.0                           TH.data_1.0-7                           digest_0.6.10                          
 [13] foreach_1.4.3                           BiocInstaller_1.22.3                    gdata_2.17.0                           
 [16] magrittr_1.5                            cluster_2.0.4                           doParallel_1.0.10                      
 [19] limma_3.28.20                           ComplexHeatmap_1.10.2                   Biostrings_2.40.2                      
 [22] readr_1.0.0                             annotate_1.50.0                         matrixStats_0.50.2                     
 [25] R.utils_2.3.0                           sandwich_2.3-4                          colorspace_1.2-6                       
 [28] rvest_0.3.2                             ggrepel_0.5                             haven_0.2.1                            
 [31] dplyr_0.5.0                             RCurl_1.95-4.8                          jsonlite_1.0                           
 [34] hexbin_1.27.1                           TxDb.Hsapiens.UCSC.hg19.knownGene_3.2.2 graph_1.50.0                           
 [37] genefilter_1.54.2                       lme4_1.1-12                             supraHex_1.10.0                        
 [40] survival_2.39-5                         zoo_1.7-13                              iterators_1.0.8                        
 [43] ape_3.5                                 gtable_0.2.0                            zlibbioc_1.18.0                        
 [46] XVector_0.12.1                          sjstats_0.4.0                           GetoptLong_0.1.4                       
 [49] sjmisc_1.8                              kernlab_0.9-24                          Rgraphviz_2.16.0                       
 [52] shape_1.4.2                             prabclus_2.2-6                          BiocGenerics_0.18.0                    
 [55] DEoptimR_1.0-6                          scales_0.4.0                            DESeq_1.24.0                           
 [58] mvtnorm_1.0-5                           DBI_0.5                                 GGally_1.2.0                           
 [61] edgeR_3.14.0                            ggthemes_3.2.0                          Rcpp_0.12.6                            
 [64] xtable_1.8-2                            matlab_1.0.2                            mclust_5.2                             
 [67] preprocessCore_1.34.0                   stats4_3.3.1                            httr_1.2.1                             
 [70] gplots_3.0.1                            RColorBrewer_1.1-2                      fpc_2.1-10                             
 [73] modeltools_0.2-21                       reshape_0.8.5                           XML_3.98-1.4                           
 [76] R.methodsS3_1.7.1                       flexmix_2.3-13                          nnet_7.3-12                            
 [79] reshape2_1.4.1                          AnnotationDbi_1.34.4                    munsell_0.4.3                          
 [82] tools_3.3.1                             downloader_0.4                          RSQLite_1.0.0                          
 [85] broom_0.4.1                             stringr_1.1.0                           knitr_1.14                             
 [88] robustbase_0.92-6                       caTools_1.17.1                          dendextend_1.3.0                       
 [91] coin_1.1-2                              EDASeq_2.6.2                            nlme_3.1-128                           
 [94] whisker_0.3-2                           R.oo_1.20.0                             xml2_1.0.0                             
 [97] biomaRt_2.28.0                          curl_1.2                                affyio_1.42.0                          
[100] tibble_1.2                              geneplotter_1.50.0                      stringi_1.1.1                          
[103] GenomicFeatures_1.24.5                  lattice_0.20-33                         trimcluster_0.1-2                      
[106] Matrix_1.2-7                            psych_1.6.6                             nloptr_1.0.4                           
[109] effects_3.1-1                           stringdist_0.9.4.1                      GlobalOptions_0.0.10                   
[112] data.table_1.9.6                        cowplot_0.6.2                           bitops_1.0-6                           
[115] dnet_1.0.9                              rtracklayer_1.32.2                      GenomicRanges_1.24.2                   
[118] R6_2.1.3                                latticeExtra_0.6-28                     affy_1.50.0                            
[121] hwriter_1.3.2                           ShortRead_1.30.0                        KernSmooth_2.23-15                     
[124] IRanges_2.6.1                           codetools_0.2-14                        MASS_7.3-45                            
[127] gtools_3.5.0                            assertthat_0.1                          chron_2.3-47                           
[130] SummarizedExperiment_1.2.3              rjson_0.2.15                            mnormt_1.5-4                           
[133] GenomicAlignments_1.8.4                 Rsamtools_1.24.0                        multcomp_1.4-6                         
[136] S4Vectors_0.10.3                        diptest_0.75-7                          parallel_3.3.1                         
[139] sjPlot_2.0.2                            grid_3.3.1                              tidyr_0.6.0                            
[142] class_7.3-14                            minqa_1.2.4

Taceback():

11: date_names_lang(date_names)
10: locale()
9: default_locale()
8: guess_header_(datasource, tokenizer, locale)
7: guess_header(ds_header, tokenizer, locale)
6: col_spec_standardise(data, skip = skip, comment = comment, n = guess_max, 
       col_names = col_names, col_types = col_`enter code here`types, tokenizer = tokenizer, 
       locale = locale)
5: read_delimited(file, tokenizer, col_names = col_names, col_types = col_types, 
       locale = locale, skip = skip, comment = comment, n_max = n_max, 
       guess_max = guess_max, progress = progress)
4: read_tsv("https://gdc-api.nci.nih.gov/projects?size=1000&format=tsv", 
       col_types = "ccccccc")
3: getGDCprojects()
2: checkProjectInput(project)
1: GDCquery(project = "TARGET-AML", data.category = "Transcriptome Profiling", 
       data.type = "Gene Expression Quantification", workflow.type = "HTSeq - Counts")