Introduction

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TCGAbiolinks is able to access The National Cancer Institute (NCI) Genomic Data Commons (GDC) thorough its
GDC Application Programming Interface (API) to search, download and prepare relevant data for analysis in R.

News

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• April 2022:
  • Started to add support for GENCODE v36 pipelines
  • Add stemness score functions
• December 2019:
  • Added support to non TCGA/TARGET projects - https://rpubs.com/tiagochst/TCGAbiolinks_RNA-seq_new_projects
  • Added support to linked Omics data retrieval - https://rpubs.com/tiagochst/linkedOmics
  • Included Glioma classifier from GUI to the main package - https://bioconductor.org/packages/devel/bioc/vignettes/TCGAbiolinks/inst/doc/classifiers.html
• Added support to BCR Biotab clinical files
  
• Workshop materials (ATAC-seq, ELMER and TCGAbiolinks) were added to vignette (https://bioconductor.org/packages/devel/bioc/vignettes/TCGAbiolinks/inst/doc/index.html)

Citation

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If you use TCGAbiolinks, please cite:

• Colaprico, Antonio, et al. “TCGAbiolinks: an R/Bioconductor package for integrative analysis of TCGA data.” Nucleic acids research 44.8 (2015): e71-e71.
• Silva, Tiago C., et al. “TCGA Workflow: Analyze cancer genomics and epigenomics data using Bioconductor packages.” F1000Research 5 (2016). (https://f1000research.com/articles/5-1542/v2)
• Mounir, Mohamed, et al. “New functionalities in the TCGAbiolinks package for the study and integration of cancer data from GDC and GTEx.” PLoS computational biology 15.3 (2019): e1006701. (https://doi.org/10.1371/journal.pcbi.1006701)

Other useful links

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• Gao, Galen F., et al. “Before and After: Comparison of Legacy and Harmonized TCGA Genomic Data Commons’ Data.” Cell systems 9.1 (2019): 24-34. (https://doi.org/10.1016/j.cels.2019.06.006)

• TCGA Workflow Analyze cancer genomics and epigenomics data using Bioconductor packages: http://bioconductor.org/packages/TCGAWorkflow/

Installation

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You can install the stable version from Bioconductor. If you are having issues with the stable version, try using the development version.

• Stable version:

if (!requireNamespace("BiocManager", quietly=TRUE))
    install.packages("BiocManager")
BiocManager::install("TCGAbiolinks")

• Development version:

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
BiocManager::install("BioinformaticsFMRP/TCGAbiolinksGUI.data")
BiocManager::install("BioinformaticsFMRP/TCGAbiolinks")

Question and issues

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Please use Github issues if you want to file bug reports or feature requests.

Required libraries

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The examples in this tutorial use the following libraries:

library(TCGAbiolinks)
library(dplyr)
library(DT)

Session info

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version

##                _                           
## platform       x86_64-pc-linux-gnu         
## arch           x86_64                      
## os             linux-gnu                   
## system         x86_64, linux-gnu           
## status                                     
## major          4                           
## minor          2.0                         
## year           2022                        
## month          04                          
## day            22                          
## svn rev        82229                       
## language       R                           
## version.string R version 4.2.0 (2022-04-22)
## nickname       Vigorous Calisthenics

packageVersion("TCGAbiolinks")

## [1] '2.24.3'