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:
## R version 3.5.1 Patched (2018-07-24 r75005)
## Platform: x86_64-w64-mingw32/x64 (64-bit)
## Running under: Windows Server 2012 R2 x64 (build 9600)
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## Matrix products: default
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## locale:
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## [2] LC_CTYPE=English_United States.1252
## [3] LC_MONETARY=English_United States.1252
## [4] LC_NUMERIC=C
## [5] LC_TIME=English_United States.1252
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## attached base packages:
## [1] grid parallel stats4 stats graphics grDevices utils
## [8] datasets methods base
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## other attached packages:
## [1] TCGAbiolinks_2.8.4 maftools_1.6.15
## [3] bindrcpp_0.2.2 png_0.1-7
## [5] DT_0.4 dplyr_0.7.6
## [7] SummarizedExperiment_1.10.1 DelayedArray_0.6.6
## [9] BiocParallel_1.14.2 matrixStats_0.54.0
## [11] Biobase_2.40.0 GenomicRanges_1.32.6
## [13] GenomeInfoDb_1.16.0 IRanges_2.14.11
## [15] S4Vectors_0.18.3 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] crayon_1.3.4 RCurl_1.95-4.11
## [37] jsonlite_1.5 roxygen2_6.1.0
## [39] genefilter_1.62.0 bindr_0.1.1
## [41] VariantAnnotation_1.26.1 survival_2.42-6
## [43] zoo_1.8-3 iterators_1.0.10
## [45] glue_1.3.0 survminer_0.4.3
## [47] registry_0.5 gtable_0.2.0
## [49] zlibbioc_1.26.0 XVector_0.20.0
## [51] GetoptLong_0.1.7 shape_1.4.4
## [53] scales_1.0.0 DESeq_1.32.0
## [55] rngtools_1.3.1 DBI_1.0.0
## [57] edgeR_3.22.3 bibtex_0.4.2
## [59] ggthemes_4.0.1 Rcpp_0.12.18
## [61] xtable_1.8-3 progress_1.2.0
## [63] cmprsk_2.2-7 mclust_5.4.1
## [65] bit_1.1-14 matlab_1.0.2
## [67] km.ci_0.5-2 htmlwidgets_1.2
## [69] httr_1.3.1 RColorBrewer_1.1-2
## [71] pkgconfig_2.0.2 XML_3.98-1.16
## [73] R.methodsS3_1.7.1 locfit_1.5-9.1
## [75] reshape2_1.4.3 later_0.7.4
## [77] labeling_0.3 tidyselect_0.2.4
## [79] rlang_0.2.2 AnnotationDbi_1.42.1
## [81] munsell_0.5.0 tools_3.5.1
## [83] downloader_0.4 RSQLite_2.1.1
## [85] devtools_1.13.6 broom_0.5.0
## [87] evaluate_0.11 stringr_1.3.1
## [89] yaml_2.2.0 knitr_1.20
## [91] bit64_0.9-7 survMisc_0.5.5
## [93] purrr_0.2.5 EDASeq_2.14.1
## [95] nlme_3.1-137 mime_0.5
## [97] R.oo_1.22.0 xml2_1.2.0
## [99] biomaRt_2.36.1 BiocStyle_2.8.2
## [101] compiler_3.5.1 curl_3.2
## [103] testthat_2.0.0 tibble_1.4.2
## [105] geneplotter_1.58.0 stringi_1.2.4
## [107] highr_0.7 GenomicFeatures_1.32.2
## [109] lattice_0.20-35 Matrix_1.2-14
## [111] commonmark_1.5 KMsurv_0.1-5
## [113] pillar_1.3.0 GlobalOptions_0.1.0
## [115] cowplot_0.9.3 data.table_1.11.4
## [117] bitops_1.0-6 httpuv_1.4.5
## [119] rtracklayer_1.40.6 R6_2.2.2
## [121] latticeExtra_0.6-28 hwriter_1.3.2
## [123] promises_1.0.1 ShortRead_1.38.0
## [125] gridExtra_2.3 codetools_0.2-15
## [127] assertthat_0.2.0 pkgmaker_0.27
## [129] rprojroot_1.3-2 rjson_0.2.20
## [131] withr_2.1.2 GenomicAlignments_1.16.0
## [133] Rsamtools_1.32.3 GenomeInfoDbData_1.1.0
## [135] mgcv_1.8-24 hms_0.4.2
## [137] tidyr_0.8.1 rmarkdown_1.10
## [139] ggpubr_0.1.8 shiny_1.1.0