Introduction

In this section, we will download the same data using TCGAbiolinks, but instead of doing it programmatically we will use TCGAbiolinksGUI (Silva et al. 2017).

First we will launch the TCGAbiolinksGUI.

library(TCGAbiolinksGUI)
TCGAbiolinksGUI()

Downloading data

Gene expression

After launching the GUI select the GDC Data/Get GDC data/Molecular data.


Fill the search fields with the same information below and click on Visualize Data. If you select Filter using clinical data under the clinical filter we will also plot the clinical information.


A plot with the summary of the data will be shown.


Also, if you want more details you can also open the GDC search results: Results section.


After the query is completed, you will be able to download the data and convert it to an R object in the Download & Prepare section.


If successful it will give you a message where the data was saved.

## Visualizing the Summarized Experiment


To visualize the SummarizedExperiment object select GDC Data/Manage SummarizedExperiment:


And click on Select Summarized Experiment file.


Select the file downloaded from GDC.


You can access sample metadata


the assay data

Accessing assay information from SummarizedExperiment

Accessing assay information from SummarizedExperiment


or the features metadata

Accessing features information from SummarizedExperiment

Accessing features information from SummarizedExperiment

DNA methylation


Again, fill the search fields with the same information below and click on Visualize Data. If you select Filter using clinical data under the clinical filter we will also plot the clinical information.


A plot with the summary of the data will be shown.


After the query is completed, you will be able to download the data and convert it to an R object in the Download & Prepare section.


If successful it will give you a message where the data was saved.

Session Info

sessionInfo()
## R version 3.4.1 (2017-06-30)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 16.04.2 LTS
## 
## Matrix products: default
## BLAS: /usr/local/lib/R/lib/libRblas.so
## LAPACK: /usr/local/lib/R/lib/libRlapack.so
## 
## locale:
##  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
##  [3] LC_TIME=en_US.UTF-8        LC_COLLATE=C              
##  [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
##  [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
##  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
## 
## attached base packages:
## [1] parallel  stats4    stats     graphics  grDevices utils     datasets 
## [8] methods   base     
## 
## other attached packages:
##  [1] Bioc2017.TCGAbiolinks.ELMER_0.0.0.9000
##  [2] SummarizedExperiment_1.7.5            
##  [3] DelayedArray_0.3.19                   
##  [4] matrixStats_0.52.2                    
##  [5] Biobase_2.37.2                        
##  [6] GenomicRanges_1.29.12                 
##  [7] GenomeInfoDb_1.13.4                   
##  [8] IRanges_2.11.12                       
##  [9] S4Vectors_0.15.5                      
## [10] BiocGenerics_0.23.0                   
## [11] TCGAbiolinks_2.5.6                    
## [12] bindrcpp_0.2                          
## [13] MultiAssayExperiment_1.3.20           
## [14] dplyr_0.7.2                           
## [15] DT_0.2                                
## [16] ELMER_2.0.1                           
## [17] ELMER.data_2.0.1                      
## 
## loaded via a namespace (and not attached):
##   [1] shinydashboard_0.6.1          R.utils_2.5.0                
##   [3] RSQLite_2.0                   AnnotationDbi_1.39.2         
##   [5] htmlwidgets_0.9               grid_3.4.1                   
##   [7] trimcluster_0.1-2             BiocParallel_1.11.4          
##   [9] devtools_1.13.2               DESeq_1.29.0                 
##  [11] munsell_0.4.3                 codetools_0.2-15             
##  [13] withr_2.0.0                   colorspace_1.3-2             
##  [15] BiocInstaller_1.27.2          knitr_1.16                   
##  [17] robustbase_0.92-7             labeling_0.3                 
##  [19] GenomeInfoDbData_0.99.1       KMsurv_0.1-5                 
##  [21] mnormt_1.5-5                  hwriter_1.3.2                
##  [23] bit64_0.9-7                   rprojroot_1.2                
##  [25] downloader_0.4                biovizBase_1.25.1            
##  [27] ggthemes_3.4.0                EDASeq_2.11.0                
##  [29] diptest_0.75-7                R6_2.2.2                     
##  [31] doParallel_1.0.10             locfit_1.5-9.1               
##  [33] AnnotationFilter_1.1.3        flexmix_2.3-14               
##  [35] reshape_0.8.6                 bitops_1.0-6                 
##  [37] assertthat_0.2.0              scales_0.4.1                 
##  [39] nnet_7.3-12                   gtable_0.2.0                 
##  [41] ensembldb_2.1.10              rlang_0.1.1                  
##  [43] genefilter_1.59.0             cmprsk_2.2-7                 
##  [45] GlobalOptions_0.0.12          splines_3.4.1                
##  [47] rtracklayer_1.37.3            lazyeval_0.2.0               
##  [49] acepack_1.4.1                 dichromat_2.0-0              
##  [51] selectr_0.3-1                 broom_0.4.2                  
##  [53] checkmate_1.8.3               yaml_2.1.14                  
##  [55] reshape2_1.4.2                GenomicFeatures_1.29.8       
##  [57] backports_1.1.0               httpuv_1.3.5                 
##  [59] Hmisc_4.0-3                   tools_3.4.1                  
##  [61] psych_1.7.5                   ggplot2_2.2.1                
##  [63] RColorBrewer_1.1-2            Rcpp_0.12.12                 
##  [65] plyr_1.8.4                    base64enc_0.1-3              
##  [67] progress_1.1.2                zlibbioc_1.23.0              
##  [69] purrr_0.2.2.2                 RCurl_1.95-4.8               
##  [71] prettyunits_1.0.2             ggpubr_0.1.4                 
##  [73] rpart_4.1-11                  GetoptLong_0.1.6             
##  [75] viridis_0.4.0                 zoo_1.8-0                    
##  [77] ggrepel_0.6.5                 cluster_2.0.6                
##  [79] magrittr_1.5                  data.table_1.10.4            
##  [81] circlize_0.4.1                survminer_0.4.0              
##  [83] mvtnorm_1.0-6                 whisker_0.3-2                
##  [85] ProtGenerics_1.9.0            aroma.light_3.7.0            
##  [87] hms_0.3                       mime_0.5                     
##  [89] evaluate_0.10.1               xtable_1.8-2                 
##  [91] XML_3.98-1.9                  mclust_5.3                   
##  [93] gridExtra_2.2.1               shape_1.4.2                  
##  [95] compiler_3.4.1                biomaRt_2.33.3               
##  [97] tibble_1.3.3                  R.oo_1.21.0                  
##  [99] htmltools_0.3.6               Formula_1.2-2                
## [101] tidyr_0.6.3                   geneplotter_1.55.0           
## [103] DBI_0.7                       matlab_1.0.2                 
## [105] ComplexHeatmap_1.15.0         MASS_7.3-47                  
## [107] fpc_2.1-10                    BiocStyle_2.5.8              
## [109] ShortRead_1.35.1              Matrix_1.2-10                
## [111] readr_1.1.1                   R.methodsS3_1.7.1            
## [113] Gviz_1.21.1                   bindr_0.1                    
## [115] km.ci_0.5-2                   pkgconfig_2.0.1              
## [117] GenomicAlignments_1.13.4      foreign_0.8-69               
## [119] plotly_4.7.1                  xml2_1.1.1                   
## [121] roxygen2_6.0.1                foreach_1.4.3                
## [123] annotate_1.55.0               XVector_0.17.0               
## [125] rvest_0.3.2                   stringr_1.2.0                
## [127] VariantAnnotation_1.23.6      digest_0.6.12                
## [129] ConsensusClusterPlus_1.41.0   Biostrings_2.45.3            
## [131] rmarkdown_1.6                 survMisc_0.5.4               
## [133] htmlTable_1.9                 dendextend_1.5.2             
## [135] edgeR_3.19.3                  curl_2.8.1                   
## [137] kernlab_0.9-25                shiny_1.0.3                  
## [139] Rsamtools_1.29.0              commonmark_1.2               
## [141] modeltools_0.2-21             rjson_0.2.15                 
## [143] nlme_3.1-131                  jsonlite_1.5                 
## [145] viridisLite_0.2.0             limma_3.33.7                 
## [147] BSgenome_1.45.1               lattice_0.20-35              
## [149] httr_1.2.1                    DEoptimR_1.0-8               
## [151] survival_2.41-3               interactiveDisplayBase_1.15.0
## [153] glue_1.1.1                    prabclus_2.2-6               
## [155] iterators_1.0.8               bit_1.1-12                   
## [157] class_7.3-14                  stringi_1.1.5                
## [159] blob_1.1.0                    AnnotationHub_2.9.5          
## [161] latticeExtra_0.6-28           memoise_1.1.0

Bibliography

Silva, Tiago C., Antonio Colaprico, Catharina Olsen, Gianluca Bontempi, Michele Ceccarelli, Benjamin P. Berman, and Houtan Noushmehr. 2017. “TCGAbiolinksGUI: A Graphical User Interface to Analyze Cancer Molecular and Clinical Data.” BioRxiv. Cold Spring Harbor Labs Journals. doi:10.1101/147496.