TCGAquery_subtype: Working with molecular subtypes data.

The Cancer Genome Atlas (TCGA) Research Network has reported integrated genome-wide studies of various diseases. We have added some of the subtypes defined by these report in our package:

TCGA dataset Link Paper Journal
ACC doi:10.1016/j.ccell.2016.04.002 Comprehensive Pan-Genomic Characterization of Adrenocortical Carcinoma. Cancer cell 2016
BRCA https://www.cell.com/cancer-cell/fulltext/S1535-6108(18)30119-3 A Comprehensive Pan-Cancer Molecular Study of Gynecologic and Breast Cancers Cancer cell 2018
BLCA http://www.cell.com/cell/fulltext/S0092-8674(17)31056-5 Comprehensive Molecular Characterization of Muscle-Invasive Bladder Cancer Cell 2017
CHOL http://www.sciencedirect.com/science/article/pii/S2211124717302140?via%3Dihub Integrative Genomic Analysis of Cholangiocarcinoma Identifies Distinct IDH-Mutant Molecular Profiles Cell Reports 2017
COAD http://www.nature.com/nature/journal/v487/n7407/abs/nature11252.html Comprehensive molecular characterization of human colon and rectal cancer Nature 2012
ESCA https://www.nature.com/articles/nature20805 Integrated genomic characterization of oesophageal carcinoma Nature 2017
GBM http://dx.doi.org/10.1016/j.cell.2015.12.028 Molecular Profiling Reveals Biologically Discrete Subsets and Pathways of Progression in Diffuse Glioma Cell 2016
HNSC http://www.nature.com/nature/journal/v517/n7536/abs/nature14129.html Comprehensive genomic characterization of head and neck squamous cell carcinomas Nature 2015
KICH http://www.sciencedirect.com/science/article/pii/S1535610814003043 The Somatic Genomic Landscape of Chromophobe Renal Cell Carcinoma Cancer cell 2014
KIRC http://www.nature.com/nature/journal/v499/n7456/abs/nature12222.html Comprehensive molecular characterization of clear cell renal cell carcinoma Nature 2013
KIRP http://www.nejm.org/doi/full/10.1056/NEJMoa1505917 Comprehensive Molecular Characterization of Papillary Renal-Cell Carcinoma NEJM 2016
LIHC http://linkinghub.elsevier.com/retrieve/pii/S0092-8674(17)30639-6 Comprehensive and Integrative Genomic Characterization of Hepatocellular Carcinoma Cell 2017
LGG http://dx.doi.org/10.1016/j.cell.2015.12.028 Molecular Profiling Reveals Biologically Discrete Subsets and Pathways of Progression in Diffuse Glioma Cell 2016
LUAD http://www.nature.com/nature/journal/v511/n7511/abs/nature13385.html Comprehensive molecular profiling of lung adenocarcinoma Nature 2014
LUSC http://www.nature.com/nature/journal/v489/n7417/abs/nature11404.html Comprehensive genomic characterization of squamous cell lung cancers Nature 2012
PAAD http://www.cell.com/cancer-cell/fulltext/S1535-6108(17)30299-4 Integrated Genomic Characterization of Pancreatic Ductal Adenocarcinoma Cancer Cell 2017
PCPG http://dx.doi.org/10.1016/j.ccell.2017.01.001 Comprehensive Molecular Characterization of Pheochromocytoma and Paraganglioma Cancer cell 2017
PRAD http://www.sciencedirect.com/science/article/pii/S0092867415013392 The Molecular Taxonomy of Primary Prostate Cancer Cell 2015
READ http://www.nature.com/nature/journal/v487/n7407/abs/nature11252.html Comprehensive molecular characterization of human colon and rectal cancer Nature 2012
SARC http://www.cell.com/cell/fulltext/S0092-8674(17)31203-5 Comprehensive and Integrated Genomic Characterization of Adult Soft Tissue Sarcomas Cell 2017
SKCM http://www.sciencedirect.com/science/article/pii/S0092867415006340 Genomic Classification of Cutaneous Melanoma Cell 2015
STAD http://www.nature.com/nature/journal/v511/n7511/abs/nature13385.html Comprehensive molecular characterization of gastric adenocarcinoma Nature 2013
THCA http://www.sciencedirect.com/science/article/pii/S0092867414012380 Integrated Genomic Characterization of Papillary Thyroid Carcinoma Cell 2014
UCEC http://www.nature.com/nature/journal/v497/n7447/abs/nature12113.html Integrated genomic characterization of endometrial carcinoma Nature 2013
UCS http://www.cell.com/cancer-cell/fulltext/S1535-6108(17)30053-3 Integrated Molecular Characterization of Uterine Carcinosarcoma Cancer Cell 2017
UVM http://www.cell.com/cancer-cell/fulltext/S1535-6108(17)30295-7 Integrative Analysis Identifies Four Molecular and Clinical Subsets in Uveal Melanoma Cancer Cell 2017

These subtypes will be automatically added in the summarizedExperiment object through GDCprepare. But you can also use the TCGAquery_subtype function to retrive this information.

A subset of the LGG subytpe is shown below:

Session Information


## R version 3.5.1 Patched (2018-07-12 r74967)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 16.04.5 LTS
## 
## Matrix products: default
## BLAS: /home/biocbuild/bbs-3.7-bioc/R/lib/libRblas.so
## LAPACK: /home/biocbuild/bbs-3.7-bioc/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] grid      parallel  stats4    stats     graphics  grDevices utils    
##  [8] datasets  methods   base     
## 
## other attached packages:
##  [1] TCGAbiolinks_2.8.4          maftools_1.6.15            
##  [3] bigmemory_4.5.33            bindrcpp_0.2.2             
##  [5] png_0.1-7                   DT_0.4                     
##  [7] dplyr_0.7.6                 SummarizedExperiment_1.10.1
##  [9] DelayedArray_0.6.5          BiocParallel_1.14.2        
## [11] matrixStats_0.54.0          Biobase_2.40.0             
## [13] GenomicRanges_1.32.6        GenomeInfoDb_1.16.0        
## [15] IRanges_2.14.11             S4Vectors_0.18.3           
## [17] BiocGenerics_0.26.0        
## 
## loaded via a namespace (and not attached):
##   [1] changepoint_2.2.2           backports_1.1.2            
##   [3] circlize_0.4.4              aroma.light_3.10.0         
##   [5] NMF_0.21.0                  plyr_1.8.4                 
##   [7] selectr_0.4-1               ConsensusClusterPlus_1.44.0
##   [9] lazyeval_0.2.1              splines_3.5.1              
##  [11] crosstalk_1.0.0             gridBase_0.4-7             
##  [13] ggplot2_3.0.0               sva_3.28.0                 
##  [15] digest_0.6.16               foreach_1.4.4              
##  [17] htmltools_0.3.6             magrittr_1.5               
##  [19] memoise_1.1.0               BSgenome_1.48.0            
##  [21] cluster_2.0.7-1             doParallel_1.0.11          
##  [23] limma_3.36.3                ComplexHeatmap_1.18.1      
##  [25] Biostrings_2.48.0           readr_1.1.1                
##  [27] annotate_1.58.0             wordcloud_2.6              
##  [29] R.utils_2.7.0               prettyunits_1.0.2          
##  [31] colorspace_1.3-2            blob_1.1.1                 
##  [33] rvest_0.3.2                 ggrepel_0.8.0              
##  [35] bigmemory.sri_0.1.3         crayon_1.3.4               
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##  [39] roxygen2_6.1.0              genefilter_1.62.0          
##  [41] bindr_0.1.1                 VariantAnnotation_1.26.1   
##  [43] survival_2.42-6             zoo_1.8-3                  
##  [45] iterators_1.0.10            glue_1.3.0                 
##  [47] survminer_0.4.3             registry_0.5               
##  [49] gtable_0.2.0                zlibbioc_1.26.0            
##  [51] XVector_0.20.0              GetoptLong_0.1.7           
##  [53] shape_1.4.4                 scales_1.0.0               
##  [55] DESeq_1.32.0                rngtools_1.3.1             
##  [57] DBI_1.0.0                   edgeR_3.22.3               
##  [59] bibtex_0.4.2                ggthemes_4.0.1             
##  [61] Rcpp_0.12.18                xtable_1.8-3               
##  [63] progress_1.2.0              cmprsk_2.2-7               
##  [65] mclust_5.4.1                bit_1.1-14                 
##  [67] matlab_1.0.2                km.ci_0.5-2                
##  [69] htmlwidgets_1.2             httr_1.3.1                 
##  [71] RColorBrewer_1.1-2          pkgconfig_2.0.2            
##  [73] XML_3.98-1.16               R.methodsS3_1.7.1          
##  [75] locfit_1.5-9.1              reshape2_1.4.3             
##  [77] later_0.7.4                 labeling_0.3               
##  [79] tidyselect_0.2.4            rlang_0.2.2                
##  [81] AnnotationDbi_1.42.1        munsell_0.5.0              
##  [83] tools_3.5.1                 downloader_0.4             
##  [85] RSQLite_2.1.1               devtools_1.13.6            
##  [87] broom_0.5.0                 evaluate_0.11              
##  [89] stringr_1.3.1               yaml_2.2.0                 
##  [91] knitr_1.20                  bit64_0.9-7                
##  [93] survMisc_0.5.5              purrr_0.2.5                
##  [95] EDASeq_2.14.1               nlme_3.1-137               
##  [97] mime_0.5                    R.oo_1.22.0                
##  [99] xml2_1.2.0                  biomaRt_2.36.1             
## [101] BiocStyle_2.8.2             compiler_3.5.1             
## [103] curl_3.2                    testthat_2.0.0             
## [105] tibble_1.4.2                geneplotter_1.58.0         
## [107] stringi_1.2.4               highr_0.7                  
## [109] GenomicFeatures_1.32.2      lattice_0.20-35            
## [111] Matrix_1.2-14               commonmark_1.5             
## [113] KMsurv_0.1-5                pillar_1.3.0               
## [115] GlobalOptions_0.1.0         cowplot_0.9.3              
## [117] data.table_1.11.4           bitops_1.0-6               
## [119] httpuv_1.4.5                rtracklayer_1.40.6         
## [121] R6_2.2.2                    latticeExtra_0.6-28        
## [123] hwriter_1.3.2               promises_1.0.1             
## [125] ShortRead_1.38.0            gridExtra_2.3              
## [127] codetools_0.2-15            assertthat_0.2.0           
## [129] pkgmaker_0.27               rprojroot_1.3-2            
## [131] rjson_0.2.20                withr_2.1.2                
## [133] GenomicAlignments_1.16.0    Rsamtools_1.32.3           
## [135] GenomeInfoDbData_1.1.0      mgcv_1.8-24                
## [137] hms_0.4.2                   tidyr_0.8.1                
## [139] rmarkdown_1.10              ggpubr_0.1.8               
## [141] shiny_1.1.0