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Build Status AppVeyor Build Status codecov.io bioc bioc bioc

TCGAbiolinks - An R/Bioconductor package for integrative analysis with TCGA data

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.

Installation from GitHub

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

BiocManager::install("BioinformaticsFMRP/TCGAbiolinks")

Installation from Bioconductor

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

BiocManager::install("TCGAbiolinks")

Docker image

TCGAbiolinks is available as Docker image (self-contained environments that contain everything needed to run the software), which can be easily run on Mac OS, Windows and Linux systems.

This PDF show how to install and execute the image.

The image can be obtained from Docker Hub: https://hub.docker.com/r/tiagochst/tcgabiolinksgui/

For more information please check: https://docs.docker.com/ and https://www.bioconductor.org/help/docker/

Manual

http://bioconductor.org/packages/devel/bioc/vignettes/TCGAbiolinks/inst/doc/tcgaBiolinks.html http://bioinformaticsfmrp.github.io/TCGAbiolinks/

Citation

Please cite both TCGAbiolinks package:

  • Colaprico A, Silva TC, Olsen C, Garofano L, Cava C, Garolini D, Sabedot T, Malta TM, Pagnotta SM, Castiglioni I, Ceccarelli M, Bontempi G and Noushmehr H. "TCGAbiolinks: an R/Bioconductor package for integrative analysis of TCGA data." Nucleic acids research (2015): gkv1507.

  • Mounir, Mohamed, Lucchetta, Marta, Silva, C T, Olsen, Catharina, Bontempi, Gianluca, Chen, Xi, Noushmehr, Houtan, Colaprico, Antonio, Papaleo, Elena (2019). “New functionalities in the TCGAbiolinks package for the study and integration of cancer data from GDC and GTEx.” PLoS computational biology, 15(3), e1006701.

  • Silva TC, Colaprico A, Olsen C et al.TCGA Workflow: Analyze cancer genomics and epigenomics data using Bioconductor packages [version 2; peer review: 1 approved, 2 approved with reservations]. F1000Research 2016, 5:1542 (https://doi.org/10.12688/f1000research.8923.2)

doi citation Altmetric

Also, if you have used ELMER analysis please cite:

  • Yao, L., Shen, H., Laird, P. W., Farnham, P. J., & Berman, B. P. "Inferring regulatory element landscapes and transcription factor networks from cancer methylomes." Genome Biol 16 (2015): 105.
  • Yao, Lijing, Benjamin P. Berman, and Peggy J. Farnham. "Demystifying the secret mission of enhancers: linking distal regulatory elements to target genes." Critical reviews in biochemistry and molecular biology 50.6 (2015): 550-573.
  • Tiago C Silva, Simon G Coetzee, Nicole Gull, Lijing Yao, Dennis J Hazelett, Houtan Noushmehr, De-Chen Lin, Benjamin P Berman, ELMER v.2: an R/Bioconductor package to reconstruct gene regulatory networks from DNA methylation and transcriptome profiles, Bioinformatics, Volume 35, Issue 11, 1 June 2019, Pages 1974–1977, https://doi.org/10.1093/bioinformatics/bty902