Tumor selection is decided using the sampleTypes data. For 'LAML' datasets,
the primary tumor code used is "03" otherwise, "01" is used.
Arguments
- multiassayexperiment
A
MultiAssayExperimentwith TCGA data as obtained fromcuratedTCGAData::curatedTCGAData()
Examples
example(getSubtypeMap)
#>
#> gtSbtM> library(curatedTCGAData)
#> Loading required package: MultiAssayExperiment
#> Loading required package: SummarizedExperiment
#> Loading required package: MatrixGenerics
#> Loading required package: matrixStats
#>
#> Attaching package: ‘matrixStats’
#> The following object is masked from ‘package:GenomicDataCommons’:
#>
#> count
#>
#> Attaching package: ‘MatrixGenerics’
#> The following objects are masked from ‘package:matrixStats’:
#>
#> colAlls, colAnyNAs, colAnys, colAvgsPerRowSet, colCollapse,
#> colCounts, colCummaxs, colCummins, colCumprods, colCumsums,
#> colDiffs, colIQRDiffs, colIQRs, colLogSumExps, colMadDiffs,
#> colMads, colMaxs, colMeans2, colMedians, colMins, colOrderStats,
#> colProds, colQuantiles, colRanges, colRanks, colSdDiffs, colSds,
#> colSums2, colTabulates, colVarDiffs, colVars, colWeightedMads,
#> colWeightedMeans, colWeightedMedians, colWeightedSds,
#> colWeightedVars, rowAlls, rowAnyNAs, rowAnys, rowAvgsPerColSet,
#> rowCollapse, rowCounts, rowCummaxs, rowCummins, rowCumprods,
#> rowCumsums, rowDiffs, rowIQRDiffs, rowIQRs, rowLogSumExps,
#> rowMadDiffs, rowMads, rowMaxs, rowMeans2, rowMedians, rowMins,
#> rowOrderStats, rowProds, rowQuantiles, rowRanges, rowRanks,
#> rowSdDiffs, rowSds, rowSums2, rowTabulates, rowVarDiffs, rowVars,
#> rowWeightedMads, rowWeightedMeans, rowWeightedMedians,
#> rowWeightedSds, rowWeightedVars
#> Loading required package: GenomicRanges
#> Loading required package: stats4
#> Loading required package: BiocGenerics
#> Loading required package: generics
#>
#> Attaching package: ‘generics’
#> The following objects are masked from ‘package:base’:
#>
#> as.difftime, as.factor, as.ordered, intersect, is.element, setdiff,
#> setequal, union
#>
#> Attaching package: ‘BiocGenerics’
#> The following objects are masked from ‘package:stats’:
#>
#> IQR, mad, sd, var, xtabs
#> The following objects are masked from ‘package:base’:
#>
#> Filter, Find, Map, Position, Reduce, anyDuplicated, aperm, append,
#> as.data.frame, basename, cbind, colnames, dirname, do.call,
#> duplicated, eval, evalq, get, grep, grepl, is.unsorted, lapply,
#> mapply, match, mget, order, paste, pmax, pmax.int, pmin, pmin.int,
#> rank, rbind, rownames, sapply, saveRDS, table, tapply, unique,
#> unsplit, which.max, which.min
#> Loading required package: S4Vectors
#>
#> Attaching package: ‘S4Vectors’
#> The following object is masked from ‘package:GenomicDataCommons’:
#>
#> expand
#> The following object is masked from ‘package:utils’:
#>
#> findMatches
#> The following objects are masked from ‘package:base’:
#>
#> I, expand.grid, unname
#> Loading required package: IRanges
#> Loading required package: GenomeInfoDb
#> Loading required package: Biobase
#> Welcome to Bioconductor
#>
#> Vignettes contain introductory material; view with
#> 'browseVignettes()'. To cite Bioconductor, see
#> 'citation("Biobase")', and for packages 'citation("pkgname")'.
#>
#> Attaching package: ‘Biobase’
#> The following object is masked from ‘package:MatrixGenerics’:
#>
#> rowMedians
#> The following objects are masked from ‘package:matrixStats’:
#>
#> anyMissing, rowMedians
#>
#> gtSbtM> gbm <- curatedTCGAData("GBM", c("RPPA*", "CNA*"), version = "2.0.1", FALSE)
#> Querying and downloading: GBM_CNACGH_CGH_hg_244a-20160128
#> see ?curatedTCGAData and browseVignettes('curatedTCGAData') for documentation
#> loading from cache
#> require(“RaggedExperiment”)
#> Querying and downloading: GBM_CNACGH_CGH_hg_415k_g4124a-20160128
#> see ?curatedTCGAData and browseVignettes('curatedTCGAData') for documentation
#> loading from cache
#> Querying and downloading: GBM_CNASNP-20160128
#> see ?curatedTCGAData and browseVignettes('curatedTCGAData') for documentation
#> loading from cache
#> Querying and downloading: GBM_RPPAArray-20160128
#> see ?curatedTCGAData and browseVignettes('curatedTCGAData') for documentation
#> loading from cache
#> Querying and downloading: GBM_colData-20160128
#> see ?curatedTCGAData and browseVignettes('curatedTCGAData') for documentation
#> loading from cache
#> Querying and downloading: GBM_metadata-20160128
#> see ?curatedTCGAData and browseVignettes('curatedTCGAData') for documentation
#> loading from cache
#> Querying and downloading: GBM_sampleMap-20160128
#> see ?curatedTCGAData and browseVignettes('curatedTCGAData') for documentation
#> loading from cache
#> harmonizing input:
#> removing 5922 sampleMap rows not in names(experiments)
#>
#> gtSbtM> getSubtypeMap(gbm)
#> GBM_annotations GBM_subtype
#> 1 Patient_ID Case
#> 2 methylation_subtypes MGMT promoter status
#> 3 mutation_subtypes IDH/codel subtype
#> 4 histological_subtypes Histology
#> 5 mrna_subtypes Original Subtype
#> 6 mrna_subtypes Transcriptome Subtype
#> 7 mrna_subtypes Pan-Glioma RNA Expression Cluster
#> 8 mrna_subtypes IDH-specific RNA Expression Cluster
#> 9 methylation_subtypes Pan-Glioma DNA Methylation Cluster
#> 10 methylation_subtypes IDH-specific DNA Methylation Cluster
#> 11 methylation_subtypes Supervised DNA Methylation Cluster
#> 12 methylation_subtypes Random Forest Sturm Cluster
#> 13 protein_subtypes RPPA cluster
#>
#> gtSbtM> sampleTables(gbm)
#> $`GBM_CNACGH_CGH_hg_244a-20160128`
#>
#> 01 10 11
#> 267 145 26
#>
#> $`GBM_CNACGH_CGH_hg_415k_g4124a-20160128`
#>
#> 01 10
#> 169 169
#>
#> $`GBM_CNASNP-20160128`
#>
#> 01 02 10 11
#> 577 13 488 26
#>
#> $`GBM_RPPAArray-20160128`
#>
#> 01 02
#> 233 11
#>
#>
#> gtSbtM> TCGAsplitAssays(gbm, c("01", "10"))
#> Warning: Some 'sampleCodes' not found in assays
#> Warning: Inconsistent barcode lengths: 28, 27
#> A MultiAssayExperiment object of 7 listed
#> experiments with user-defined names and respective classes.
#> Containing an ExperimentList class object of length 7:
#> [1] 01_GBM_CNACGH_CGH_hg_244a-20160128: RaggedExperiment with 81512 rows and 267 columns
#> [2] 10_GBM_CNACGH_CGH_hg_244a-20160128: RaggedExperiment with 81512 rows and 145 columns
#> [3] 01_GBM_CNACGH_CGH_hg_415k_g4124a-20160128: RaggedExperiment with 57975 rows and 169 columns
#> [4] 10_GBM_CNACGH_CGH_hg_415k_g4124a-20160128: RaggedExperiment with 57975 rows and 169 columns
#> [5] 01_GBM_CNASNP-20160128: RaggedExperiment with 602338 rows and 577 columns
#> [6] 10_GBM_CNASNP-20160128: RaggedExperiment with 602338 rows and 488 columns
#> [7] 01_GBM_RPPAArray-20160128: SummarizedExperiment with 208 rows and 233 columns
#> Functionality:
#> experiments() - obtain the ExperimentList instance
#> colData() - the primary/phenotype DataFrame
#> sampleMap() - the sample coordination DataFrame
#> `$`, `[`, `[[` - extract colData columns, subset, or experiment
#> *Format() - convert into a long or wide DataFrame
#> assays() - convert ExperimentList to a SimpleList of matrices
#> exportClass() - save data to flat files
#>
#> gtSbtM> getClinicalNames("COAD")
#> [1] "years_to_birth"
#> [2] "vital_status"
#> [3] "days_to_death"
#> [4] "days_to_last_followup"
#> [5] "tumor_tissue_site"
#> [6] "pathologic_stage"
#> [7] "pathology_T_stage"
#> [8] "pathology_N_stage"
#> [9] "pathology_M_stage"
#> [10] "gender"
#> [11] "date_of_initial_pathologic_diagnosis"
#> [12] "days_to_last_known_alive"
#> [13] "radiation_therapy"
#> [14] "histological_type"
#> [15] "residual_tumor"
#> [16] "number_of_lymph_nodes"
#> [17] "race"
#> [18] "ethnicity"
TCGAprimaryTumors(gbm)
#> harmonizing input:
#> removing 878 sampleMap rows with 'colname' not in colnames of experiments
#> removing 2 colData rownames not in sampleMap 'primary'
#> A MultiAssayExperiment object of 4 listed
#> experiments with user-defined names and respective classes.
#> Containing an ExperimentList class object of length 4:
#> [1] GBM_CNACGH_CGH_hg_244a-20160128: RaggedExperiment with 81512 rows and 267 columns
#> [2] GBM_CNACGH_CGH_hg_415k_g4124a-20160128: RaggedExperiment with 57975 rows and 169 columns
#> [3] GBM_CNASNP-20160128: RaggedExperiment with 602338 rows and 577 columns
#> [4] GBM_RPPAArray-20160128: SummarizedExperiment with 208 rows and 233 columns
#> Functionality:
#> experiments() - obtain the ExperimentList instance
#> colData() - the primary/phenotype DataFrame
#> sampleMap() - the sample coordination DataFrame
#> `$`, `[`, `[[` - extract colData columns, subset, or experiment
#> *Format() - convert into a long or wide DataFrame
#> assays() - convert ExperimentList to a SimpleList of matrices
#> exportClass() - save data to flat files