TCGAbiolinks: an R/Bioconductor package for integrative analysis of TCGA data

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ID: 289863
2015
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Abstract
The Cancer Genome Atlas (TCGA) research network has made public a large collection of clinical and molecular phenotypes of more than 10 000 tumor patients across 33 different tumor types. Using this cohort, TCGA has published over 20 marker papers detailing the genomic and epigenomic alterations associated with these tumor types. Although many important discoveries have been made by TCGA's research network, opportunities still exist to implement novel methods, thereby elucidating new biological pathways and diagnostic markers. However, mining the TCGA data presents several bioinformatics challenges, such as data retrieval and integration with clinical data and other molecular data types (e.g. RNA and DNA methylation). We developed an R/Bioconductor package called TCGAbiolinks to address these challenges and offer bioinformatics solutions by using a guided workflow to allow users to query, download and perform integrative analyses of TCGA data. We combined methods from computer science and statistics into the pipeline and incorporated methodologies developed in previous TCGA marker studies and in our own group. Using four different TCGA tumor types (Kidney, Brain, Breast and Colon) as examples, we provide case studies to illustrate examples of reproducibility, integrative analysis and utilization of different Bioconductor packages to advance and accelerate novel discoveries.
Reference Key
openalex_W2230320310 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Antonio Colaprico, Tiago C. Silva, Catharina Olsen, Luciano Garofano, Claudia Cava, Davide Garolini, Thaís S. Sabedot, Tathiane M. Malta, Stefano Maria Pagnotta, Isabella Castiglioni, Michele Ceccarelli, Gianluca Bontempi, Houtan Noushmehr
Journal Nucleic Acids Research
Year 2015
DOI
10.1093/nar/gkv1507
URL
https://academic.oup.com/nar/article-pdf/44/8/e71/28654934/gkv1507.pdf
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