Managing data from large scale projects such as The Cancer Genome Atlas (TCGA)(Cancer Genome Atlas Research Network 2008) for further analysis is an important and time consuming step for research projects. Several efforts, such as Firehose project, make TCGA pre-processed data publicly available via web services and data portals but it requires managing, downloading and preparing the data for following steps. We developed an open source and extensible R based data client for Firehose Level 3 and Level 4 data and demonstrated its use with sample case studies. RTCGAToolbox could improve data management for researchers who are interested with TCGA data. In addition, it can be integrated with other analysis pipelines for further data analysis.
RTCGAToolbox is open-source and licensed under the GNU General Public License Version 2.0. All documentation and source code for RTCGAToolbox is freely available. Please site the paper at (Samur MK. 2014).
Currently, following functions are provided to access datasets and process datasets.
To install RTCGAToolbox, you can use Bioconductor. Source code is also available on GitHub. First time users use the following code snippet to install the package
if (!requireNamespace("BiocManager"))
install.packages("BiocManager")
BiocManager::install("RTCGAToolbox")Before getting the data from Firehose pipelines, users have to check valid dataset aliases, stddata run dates and analyze run dates. To provide valid information RTCGAToolbox comes with three control functions. Users can list datasets with “getFirehoseDatasets” function. In addition, users have to provide stddata run date or/and analyze run date for client function. Valid dates are accessible via “getFirehoseRunningDates” and “getFirehoseAnalyzeDates” functions. Below code chunk shows how to list datasets and dates.
library(RTCGAToolbox)
# Valid aliases
getFirehoseDatasets()## [1] "ACC" "BLCA" "BRCA" "CESC" "CHOL" "COADREAD"
## [7] "COAD" "DLBC" "ESCA" "FPPP" "GBMLGG" "GBM"
## [13] "HNSC" "KICH" "KIPAN" "KIRC" "KIRP" "LAML"
## [19] "LGG" "LIHC" "LUAD" "LUSC" "MESO" "OV"
## [25] "PAAD" "PCPG" "PRAD" "READ" "SARC" "SKCM"
## [31] "STAD" "STES" "TGCT" "THCA" "THYM" "UCEC"
## [37] "UCS" "UVM"# Valid stddata runs
getFirehoseRunningDates(last = 3)## [1] "20160128" "20151101" "20150821"# Valid analysis running dates (will return 3 recent date)
getFirehoseAnalyzeDates(last=3)## [1] "20160128" "20150821" "20150402"When the dates and datasets are determined users can call data client function (“getFirehoseData”) to access data. Current version can download multiple data types except ISOFORM and exon level data due to their huge data size. Below code chunk will download READ dataset with clinical and mutation data.
# READ mutation data and clinical data
brcaData <- getFirehoseData(dataset="READ", runDate="20160128",
forceDownload=TRUE, clinical=TRUE, Mutation=TRUE)Printing the object will show the user what datasets are in the FirehoseData
object:
brcaData## READ FirehoseData objectStandard run date: 20160128
## Analysis running date: NA
## Available data types:
## clinical: A data frame of phenotype data, dim: 171 x 19
## Mutation: A data.frame, dim: 22075 x 39
## To export data, use the 'getData' function.Users have to set several parameters to get data they need. Below “getFirehoseData” options has been explained:
getFirehoseDatasets() like as explained
above.getFirehoseRunningDates().Following logic keys are provided for different data types. By default client only download clinical data.
Users can also set following parameters to set client behavior.
We’ve provided an abbreviated dataset from the ‘ACC’ (Adrenocortical carcinoma) that contains only the top 6 rows for each dataset and a full clinical dataset. This dataset can be invoked by doing:
data(accmini)
accmini## ACC FirehoseData objectStandard run date: 20160128
## Analysis running date: 20160128
## Available data types:
## clinical: A data frame of phenotype data, dim: 92 x 18
## RNASeq2Gene: A matrix of count or scaled estimate data, dim: 6 x 79
## RNASeq2GeneNorm: A list of FirehosemRNAArray object(s), length: 1
## miRNASeqGene: A matrix, dim: 6 x 80
## CNASNP: A data.frame, dim: 6 x 6
## CNVSNP: A data.frame, dim: 6 x 6
## Methylation: A list of FirehoseMethylationArray object(s), length: 1
## RPPAArray: A list of FirehosemRNAArray object(s), length: 1
## GISTIC: A FirehoseGISTIC for copy number data
## Mutation: A data.frame, dim: 6 x 52
## To export data, use the 'getData' function.accmini data is a FirehoseData object that stores RNAseq, copy number,
mutation, clinical data from the Adrenocortical Carcinoma (ACC) study.The biocExtract function allows the user to take any downloaded dataset and
convert it into a standard Bioconductor object. These can either be a
SummarizedExperiment, RangedSummarizedExperiment, or RaggedExperiment
based on features of the data. The user must provide the desired data type
as input to the function along with the actual FirehoseData data object.
This allows for easy adaptability to other software in the Bioconductor
ecosystem.
biocExtract(accmini, "RNASeq2Gene")## working on: RNASeq2Gene## class: SummarizedExperiment
## dim: 6 79
## metadata(0):
## assays(1): ''
## rownames(6): A1BG A1CF ... A2ML1 A2M
## rowData names(0):
## colnames(79): TCGA-OR-A5J1-01A-11R-A29S-07 TCGA-OR-A5J2-01A-11R-A29S-07
## ... TCGA-PK-A5HA-01A-11R-A29S-07 TCGA-PK-A5HB-01A-11R-A29S-07
## colData names(0):biocExtract(accmini, "CNASNP")## working on: CNASNP## class: RangedSummarizedExperiment
## dim: 6 1
## metadata(0):
## assays(2): Num_Probes Segment_Mean
## rownames: NULL
## rowData names(0):
## colnames(1): TCGA-OR-A5J1-10A-01D-A29K-01
## colData names(0):You can obtain the downloaded data in tabular or list format from the
FirehoseData object by using ‘getData()’ function.
head(getData(accmini, "clinical"))## Composite Element REF years_to_birth vital_status days_to_death
## tcga.or.a5k0 value 69 0 <NA>
## tcga.or.a5kp value 45 0 <NA>
## tcga.or.a5l5 value 77 0 <NA>
## tcga.or.a5lb value 59 1 1204
## tcga.p6.a5og value 45 1 383
## tcga.pk.a5hb value 63 0 <NA>
## days_to_last_followup tumor_tissue_site pathologic_stage
## tcga.or.a5k0 1029 adrenal stage ii
## tcga.or.a5kp 2777 adrenal stage ii
## tcga.or.a5l5 1317 adrenal stage i
## tcga.or.a5lb <NA> adrenal stage iv
## tcga.p6.a5og <NA> adrenal stage iv
## tcga.pk.a5hb 1293 adrenal <NA>
## pathology_T_stage pathology_N_stage pathology_M_stage gender
## tcga.or.a5k0 t2 n0 <NA> female
## tcga.or.a5kp t2 n0 <NA> female
## tcga.or.a5l5 t1 n0 <NA> female
## tcga.or.a5lb t4 n0 <NA> male
## tcga.p6.a5og t4 n0 <NA> female
## tcga.pk.a5hb <NA> <NA> <NA> male
## date_of_initial_pathologic_diagnosis radiation_therapy
## tcga.or.a5k0 2009 no
## tcga.or.a5kp 2006 no
## tcga.or.a5l5 2010 no
## tcga.or.a5lb 2006 yes
## tcga.p6.a5og 2011 no
## tcga.pk.a5hb 2003 yes
## histological_type residual_tumor
## tcga.or.a5k0 adrenocortical carcinoma- usual type r0
## tcga.or.a5kp adrenocortical carcinoma- usual type r0
## tcga.or.a5l5 adrenocortical carcinoma- usual type r0
## tcga.or.a5lb adrenocortical carcinoma- usual type r0
## tcga.p6.a5og adrenocortical carcinoma- usual type r2
## tcga.pk.a5hb adrenocortical carcinoma- usual type <NA>
## number_of_lymph_nodes race ethnicity
## tcga.or.a5k0 <NA> white <NA>
## tcga.or.a5kp 0 white not hispanic or latino
## tcga.or.a5l5 <NA> white not hispanic or latino
## tcga.or.a5lb <NA> white not hispanic or latino
## tcga.p6.a5og 0 white not hispanic or latino
## tcga.pk.a5hb <NA> <NA> <NA>getData(accmini, "RNASeq2GeneNorm")## [[1]]## gdac.broadinstitute.org_ACC.Merge_rnaseqv2__illuminahiseq_rnaseqv2__unc_edu__Level_3__RSEM_genes_normalized__data.Level_3.2016012800.0.0.tar.gz## FirehoseCGHArray object, dim: 6 79getData(accmini, "GISTIC", "AllByGene")## Gene.Symbol Locus.ID Cytoband TCGA.OR.A5J1.01A.11D.A29H.01
## 1 ACAP3 116983 1p36.33 0.030
## 2 ACTRT2 140625 1p36.32 0.030
## 3 AGRN 375790 1p36.33 0.030
## 4 ANKRD65 441869 1p36.33 0.030
## 5 ATAD3A 55210 1p36.33 0.030
## 6 ATAD3B 83858 1p36.33 0.030
## TCGA.OR.A5J2.01A.11D.A29H.01 TCGA.OR.A5J3.01A.11D.A29H.01
## 1 -0.070 -0.065
## 2 -0.070 -0.065
## 3 -0.070 -0.065
## 4 -0.070 -0.065
## 5 -0.070 -0.065
## 6 -0.070 -0.065
## TCGA.OR.A5J4.01A.11D.A29H.01 TCGA.OR.A5J5.01A.11D.A29H.01
## 1 0.753 -0.029
## 2 0.753 -0.029
## 3 0.753 -0.029
## 4 0.753 -0.029
## 5 0.753 -0.029
## 6 0.753 -0.029
## TCGA.OR.A5J6.01A.31D.A29H.01 TCGA.OR.A5J7.01A.11D.A29H.01
## 1 -0.010 -0.339
## 2 -0.010 -0.339
## 3 -0.010 -0.339
## 4 -0.010 -0.339
## 5 -0.010 -0.339
## 6 -0.010 -0.339
## TCGA.OR.A5J8.01A.11D.A29H.01 TCGA.OR.A5J9.01A.11D.A29H.01
## 1 -0.007 -0.915
## 2 -0.007 -0.915
## 3 -0.007 -0.915
## 4 -0.007 -0.915
## 5 -0.007 -0.915
## 6 -0.007 -0.915
## TCGA.OR.A5JA.01A.11D.A29H.01 TCGA.OR.A5JB.01A.11D.A29H.01
## 1 0.000 0.635
## 2 0.000 0.635
## 3 0.000 0.635
## 4 0.000 0.635
## 5 0.000 0.635
## 6 0.000 0.635
## TCGA.OR.A5JC.01A.11D.A29H.01 TCGA.OR.A5JD.01A.11D.A29H.01
## 1 -0.244 -0.772
## 2 -0.244 -0.772
## 3 -0.244 -0.772
## 4 -0.244 -0.772
## 5 -0.244 -0.772
## 6 -0.244 -0.772
## TCGA.OR.A5JE.01A.11D.A29H.01 TCGA.OR.A5JF.01A.11D.A29H.01
## 1 -0.554 -0.024
## 2 -0.554 -0.024
## 3 -0.554 -0.024
## 4 -0.554 -0.024
## 5 -0.554 -0.024
## 6 -0.554 -0.024
## TCGA.OR.A5JG.01A.11D.A29H.01 TCGA.OR.A5JH.01A.11D.A309.01
## 1 -0.058 -0.237
## 2 -0.058 -0.237
## 3 -0.058 -0.237
## 4 -0.058 -0.237
## 5 -0.058 -0.237
## 6 -0.058 -0.237
## TCGA.OR.A5JI.01A.11D.A29H.01 TCGA.OR.A5JJ.01A.11D.A29H.01
## 1 -0.421 -0.124
## 2 -0.421 -0.124
## 3 -0.421 -0.124
## 4 -0.421 -0.124
## 5 -0.421 -0.124
## 6 -0.421 -0.124
## TCGA.OR.A5JK.01A.11D.A29H.01 TCGA.OR.A5JL.01A.11D.A29H.01
## 1 -0.355 -0.073
## 2 -0.355 -0.073
## 3 -0.355 -0.073
## 4 -0.355 -0.073
## 5 -0.355 -0.073
## 6 -0.355 -0.073
## TCGA.OR.A5JM.01A.11D.A29H.01 TCGA.OR.A5JO.01A.11D.A29H.01
## 1 -0.560 0.001
## 2 -0.560 0.001
## 3 -0.560 0.001
## 4 -0.560 0.001
## 5 -0.560 0.001
## 6 -0.560 0.001
## TCGA.OR.A5JP.01A.11D.A29H.01 TCGA.OR.A5JQ.01A.11D.A29H.01
## 1 -0.573 -0.388
## 2 -0.573 -0.388
## 3 -0.573 -0.388
## 4 -0.573 -0.388
## 5 -0.573 -0.388
## 6 -0.573 -0.388
## TCGA.OR.A5JR.01A.11D.A29H.01 TCGA.OR.A5JS.01A.11D.A29H.01
## 1 0.071 -0.858
## 2 0.071 -0.858
## 3 0.071 -0.858
## 4 0.071 -0.858
## 5 0.071 -0.858
## 6 0.071 -0.858
## TCGA.OR.A5JT.01A.11D.A29H.01 TCGA.OR.A5JU.01A.11D.A309.01
## 1 0.043 -0.053
## 2 0.043 -0.053
## 3 0.043 -0.053
## 4 0.043 -0.053
## 5 0.043 -0.053
## 6 0.043 -0.053
## TCGA.OR.A5JV.01A.11D.A29H.01 TCGA.OR.A5JW.01A.11D.A29H.01
## 1 -0.602 -0.802
## 2 -0.602 -0.802
## 3 -0.602 -0.802
## 4 -0.602 -0.802
## 5 -0.602 -0.802
## 6 -0.602 -0.802
## TCGA.OR.A5JX.01A.11D.A29H.01 TCGA.OR.A5JY.01A.31D.A29H.01
## 1 -0.581 -0.334
## 2 -0.581 -0.334
## 3 -0.581 -0.334
## 4 -0.581 -0.334
## 5 -0.581 -0.334
## 6 -0.581 -0.334
## TCGA.OR.A5JZ.01A.11D.A29H.01 TCGA.OR.A5K0.01A.11D.A29H.01
## 1 -0.031 -0.046
## 2 -0.031 -0.046
## 3 -0.031 -0.046
## 4 -0.031 -0.046
## 5 -0.031 -0.046
## 6 -0.031 -0.046
## TCGA.OR.A5K1.01A.11D.A29H.01 TCGA.OR.A5K2.01A.11D.A29H.01
## 1 0.000 -0.610
## 2 0.000 -0.610
## 3 0.000 -0.610
## 4 0.000 -0.610
## 5 0.000 -0.610
## 6 0.000 -0.610
## TCGA.OR.A5K3.01A.11D.A29H.01 TCGA.OR.A5K4.01A.11D.A29H.01
## 1 -0.075 0.018
## 2 -0.075 0.018
## 3 -0.075 0.018
## 4 -0.075 0.018
## 5 -0.075 0.018
## 6 -0.075 0.018
## TCGA.OR.A5K5.01A.11D.A29H.01 TCGA.OR.A5K6.01A.11D.A29H.01
## 1 -0.610 -0.926
## 2 -0.610 -0.926
## 3 -0.610 -0.926
## 4 -0.610 -0.926
## 5 -0.610 -0.926
## 6 -0.610 -0.926
## TCGA.OR.A5K8.01A.11D.A29H.01 TCGA.OR.A5K9.01A.11D.A29H.01
## 1 -0.019 -0.579
## 2 -0.019 -0.579
## 3 -0.019 -0.579
## 4 -0.019 -0.579
## 5 -0.019 -0.579
## 6 -0.019 -0.579
## TCGA.OR.A5KB.01A.11D.A309.01 TCGA.OR.A5KO.01A.11D.A29H.01
## 1 0.514 -0.034
## 2 0.514 -0.034
## 3 0.514 -0.034
## 4 0.514 -0.034
## 5 0.514 -0.034
## 6 0.514 -0.034
## TCGA.OR.A5KP.01A.11D.A309.01 TCGA.OR.A5KQ.01A.11D.A309.01
## 1 -0.031 0.013
## 2 -0.031 0.013
## 3 -0.031 0.013
## 4 -0.031 0.013
## 5 -0.031 0.013
## 6 -0.031 0.013
## TCGA.OR.A5KS.01A.11D.A309.01 TCGA.OR.A5KT.01A.11D.A29H.01
## 1 -0.069 0.029
## 2 -0.069 0.029
## 3 -0.069 0.029
## 4 -0.069 0.029
## 5 -0.069 0.029
## 6 -0.069 0.029
## TCGA.OR.A5KU.01A.11D.A29H.01 TCGA.OR.A5KV.01A.11D.A29H.01
## 1 -0.038 -0.001
## 2 -0.038 -0.001
## 3 -0.038 -0.001
## 4 -0.038 -0.001
## 5 -0.038 -0.001
## 6 -0.038 -0.001
## TCGA.OR.A5KW.01A.11D.A29H.01 TCGA.OR.A5KX.01A.11D.A29H.01
## 1 -0.015 -0.449
## 2 -0.015 -0.449
## 3 -0.015 -0.449
## 4 -0.015 -0.449
## 5 -0.015 -0.449
## 6 -0.015 -0.449
## TCGA.OR.A5KY.01A.11D.A29H.01 TCGA.OR.A5KZ.01A.11D.A29H.01
## 1 -0.009 -0.101
## 2 -0.009 -0.101
## 3 -0.009 -0.101
## 4 -0.009 -0.101
## 5 -0.009 -0.101
## 6 -0.009 -0.101
## TCGA.OR.A5L1.01A.11D.A309.01 TCGA.OR.A5L2.01A.11D.A309.01
## 1 -0.062 -0.277
## 2 -0.062 -0.277
## 3 -0.062 -0.277
## 4 -0.062 -0.277
## 5 -0.062 -0.277
## 6 -0.062 -0.277
## TCGA.OR.A5L3.01A.11D.A29H.01 TCGA.OR.A5L4.01A.11D.A29H.01
## 1 0.074 -0.014
## 2 0.074 -0.014
## 3 0.074 -0.014
## 4 0.074 -0.014
## 5 0.074 -0.014
## 6 0.074 -0.014
## TCGA.OR.A5L5.01A.11D.A29H.01 TCGA.OR.A5L6.01A.11D.A29H.01
## 1 0.000 -0.476
## 2 0.000 -0.476
## 3 0.000 -0.476
## 4 0.000 -0.476
## 5 0.000 -0.476
## 6 0.000 -0.476
## TCGA.OR.A5L8.01A.11D.A29H.01 TCGA.OR.A5L9.01A.11D.A29H.01
## 1 -0.028 -0.002
## 2 -0.028 -0.002
## 3 -0.028 -0.002
## 4 -0.028 -0.002
## 5 -0.028 -0.002
## 6 -0.028 -0.002
## TCGA.OR.A5LA.01A.11D.A29H.01 TCGA.OR.A5LB.01A.11D.A29H.01
## 1 -0.001 -0.068
## 2 -0.001 -0.068
## 3 -0.001 -0.068
## 4 -0.001 -0.068
## 5 -0.001 -0.068
## 6 -0.001 -0.068
## TCGA.OR.A5LC.01A.11D.A29H.01 TCGA.OR.A5LD.01A.11D.A29H.01
## 1 -0.829 -0.001
## 2 -0.829 -0.001
## 3 -0.829 -0.001
## 4 -0.829 -0.001
## 5 -0.829 -0.001
## 6 -0.829 -0.001
## TCGA.OR.A5LE.01A.11D.A29H.01 TCGA.OR.A5LF.01A.11D.A309.01
## 1 0.041 0.109
## 2 0.041 0.109
## 3 0.041 0.109
## 4 0.041 0.109
## 5 0.041 0.109
## 6 0.041 0.109
## TCGA.OR.A5LG.01A.11D.A29H.01 TCGA.OR.A5LH.01A.11D.A29H.01
## 1 -0.847 0.032
## 2 -0.847 0.032
## 3 -0.847 0.032
## 4 -0.847 0.032
## 5 -0.847 0.032
## 6 -0.847 0.032
## TCGA.OR.A5LI.01A.11D.A309.01 TCGA.OR.A5LJ.01A.11D.A29H.01
## 1 -0.884 -0.014
## 2 -0.884 -0.014
## 3 -0.884 -0.014
## 4 -0.884 -0.014
## 5 -0.884 -0.014
## 6 -0.884 -0.014
## TCGA.OR.A5LK.01A.11D.A29H.01 TCGA.OR.A5LL.01A.11D.A29H.01
## 1 0.031 -0.011
## 2 0.031 -0.011
## 3 0.031 -0.011
## 4 0.031 -0.011
## 5 0.031 -0.011
## 6 0.031 -0.011
## TCGA.OR.A5LM.01A.11D.A29H.01 TCGA.OR.A5LN.01A.11D.A29H.01
## 1 -0.440 -0.563
## 2 -0.440 -0.563
## 3 -0.440 -0.563
## 4 -0.440 -0.563
## 5 -0.440 -0.563
## 6 -0.440 -0.563
## TCGA.OR.A5LO.01A.11D.A29H.01 TCGA.OR.A5LP.01A.11D.A29H.01
## 1 0.004 -0.002
## 2 0.004 -0.002
## 3 0.004 -0.002
## 4 0.004 -0.002
## 5 0.004 -0.002
## 6 0.004 -0.002
## TCGA.OR.A5LR.01A.11D.A29H.01 TCGA.OR.A5LS.01A.11D.A29H.01
## 1 -0.001 -0.523
## 2 -0.001 -0.523
## 3 -0.001 -0.523
## 4 -0.001 -0.523
## 5 -0.001 -0.523
## 6 -0.001 -0.523
## TCGA.OR.A5LT.01A.11D.A29H.01 TCGA.OU.A5PI.01A.12D.A29H.01
## 1 -0.168 -0.545
## 2 -0.168 -0.545
## 3 -0.168 -0.545
## 4 -0.168 -0.545
## 5 -0.168 -0.545
## 6 -0.168 -0.545
## TCGA.P6.A5OG.01A.22D.A29H.01 TCGA.P6.A5OH.01A.11D.A309.01
## 1 0.221 -1.057
## 2 0.221 -1.057
## 3 0.221 -1.057
## 4 0.221 -1.057
## 5 0.221 -1.057
## 6 0.221 -1.057
## TCGA.PA.A5YG.01A.11D.A29H.01 TCGA.PK.A5H9.01A.11D.A29H.01
## 1 -0.009 0.012
## 2 -0.009 0.012
## 3 -0.009 0.012
## 4 -0.009 0.012
## 5 -0.009 0.012
## 6 -0.009 0.012
## TCGA.PK.A5HA.01A.11D.A29H.01 TCGA.PK.A5HB.01A.11D.A29H.01
## 1 -0.812 -0.056
## 2 -0.812 -0.056
## 3 -0.812 -0.056
## 4 -0.812 -0.056
## 5 -0.812 -0.056
## 6 -0.812 -0.056
## TCGA.PK.A5HC.01A.11D.A309.01
## 1 0.534
## 2 0.534
## 3 0.534
## 4 0.534
## 5 0.534
## 6 0.534sessionInfo()## R version 4.2.3 (2023-03-15)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 20.04.6 LTS
##
## Matrix products: default
## BLAS: /home/biocbuild/bbs-3.16-bioc/R/lib/libRblas.so
## LAPACK: /home/biocbuild/bbs-3.16-bioc/R/lib/libRlapack.so
##
## locale:
## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
## [3] LC_TIME=en_GB 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] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] RTCGAToolbox_2.28.4 BiocStyle_2.26.0
##
## loaded via a namespace (and not attached):
## [1] bitops_1.0-7 matrixStats_0.63.0
## [3] bit64_4.0.5 filelock_1.0.2
## [5] progress_1.2.2 httr_1.4.5
## [7] GenomicDataCommons_1.22.1 GenomeInfoDb_1.34.9
## [9] tools_4.2.3 bslib_0.4.2
## [11] utf8_1.2.3 R6_2.5.1
## [13] DBI_1.1.3 BiocGenerics_0.44.0
## [15] tidyselect_1.2.0 prettyunits_1.1.1
## [17] TCGAutils_1.18.0 bit_4.0.5
## [19] curl_5.0.0 compiler_4.2.3
## [21] cli_3.6.1 rvest_1.0.3
## [23] Biobase_2.58.0 xml2_1.3.3
## [25] DelayedArray_0.24.0 rtracklayer_1.58.0
## [27] bookdown_0.33 sass_0.4.5
## [29] readr_2.1.4 rappdirs_0.3.3
## [31] RCircos_1.2.2 stringr_1.5.0
## [33] digest_0.6.31 Rsamtools_2.14.0
## [35] rmarkdown_2.21 XVector_0.38.0
## [37] pkgconfig_2.0.3 htmltools_0.5.5
## [39] MatrixGenerics_1.10.0 dbplyr_2.3.2
## [41] fastmap_1.1.1 limma_3.54.2
## [43] rlang_1.1.0 RSQLite_2.3.0
## [45] jquerylib_0.1.4 BiocIO_1.8.0
## [47] generics_0.1.3 jsonlite_1.8.4
## [49] BiocParallel_1.32.6 dplyr_1.1.1
## [51] RCurl_1.98-1.12 magrittr_2.0.3
## [53] GenomeInfoDbData_1.2.9 Matrix_1.5-3
## [55] S4Vectors_0.36.2 fansi_1.0.4
## [57] lifecycle_1.0.3 stringi_1.7.12
## [59] yaml_2.3.7 RaggedExperiment_1.22.0
## [61] RJSONIO_1.3-1.8 SummarizedExperiment_1.28.0
## [63] zlibbioc_1.44.0 BiocFileCache_2.6.1
## [65] grid_4.2.3 blob_1.2.4
## [67] parallel_4.2.3 crayon_1.5.2
## [69] lattice_0.20-45 Biostrings_2.66.0
## [71] splines_4.2.3 GenomicFeatures_1.50.4
## [73] hms_1.1.3 KEGGREST_1.38.0
## [75] knitr_1.42 pillar_1.9.0
## [77] GenomicRanges_1.50.2 rjson_0.2.21
## [79] codetools_0.2-19 biomaRt_2.54.1
## [81] stats4_4.2.3 XML_3.99-0.14
## [83] glue_1.6.2 evaluate_0.20
## [85] data.table_1.14.8 BiocManager_1.30.20
## [87] MultiAssayExperiment_1.24.0 vctrs_0.6.1
## [89] png_0.1-8 tzdb_0.3.0
## [91] cachem_1.0.7 xfun_0.38
## [93] restfulr_0.0.15 survival_3.5-5
## [95] tibble_3.2.1 GenomicAlignments_1.34.1
## [97] AnnotationDbi_1.60.2 memoise_2.0.1
## [99] IRanges_2.32.0Cancer Genome Atlas Research Network. 2008. “Comprehensive Genomic Characterization Defines Human Glioblastoma Genes and Core Pathways.”
Mermel, C. H. and Schumacher, S. E. and Hill, B. and Meyerson, M. L. and Beroukhim, R. and Getz, G. 2011. “GISTIC2.0 Facilitates Sensitive and Confident Localization of the Targets of Focal Somatic Copy-Number Alteration in Human Cancers.”
Samur MK. 2014. “RTCGAToolbox: A New Tool for Exporting TCGA Firehose Data.”