Evidence map›Paper›PMID 26704973›Full record

ArticleNucleic acids research2016

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

Antonio Colaprico, Tiago C Silva, Catharina Olsen, Luciano Garofano, Claudia Cava, Davide Garolini, Thais S Sabedot, Tathiane M Malta, Stefano M Pagnotta, Isabella Castiglioni and 3 more

Abstract read
In one paragraph

Article in Nucleic acids research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2,657 papers.

0numbers the graph read from it
0cells of the map it votes in
2,657citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2,657 citing papers in PubMed.

  1. Review
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  3. Integrative in silico and clinical validation of urinary lncRNAs (SNHG7 & LINC00675) and β-catenin mRNA as molecular markers for early bladder cancer detection.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
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  9. SSX1 and TRIM58 expression stratifies lung squamous cell carcinoma by tumor immune microenvironment characteristics and informs potential immunotherapy responsiveness.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
    Article
  10. Review
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2,597 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Antonio ColapricoInteruniversity Institute of Bioinformatics in Brussels (IB), Brussels, Belgium Machine Learning Group (MLG), Department d'Informatique, Université libre de Bruxelles (ULB), Brussels, Belgium.
Tiago C SilvaDepartment of Genetics Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, São Paulo, Brazil Center for Integrative Systems Biology - CISBi, NAP/USP, Ribeirão Preto, São Paulo, Brazil.
Catharina OlsenInteruniversity Institute of Bioinformatics in Brussels (IB), Brussels, Belgium Machine Learning Group (MLG), Department d'Informatique, Université libre de Bruxelles (ULB), Brussels, Belgium.
Luciano GarofanoDepartment of Science and Technology, University of Sannio, Benevento, Italy Unlimited Software srl, Naples, Italy.ORCID 0000-0001-8582-0865
Claudia CavaInstitute of Molecular Bioimaging and Physiology of the National Research Council (IBFM-CNR), Milan, Italy.
Davide GaroliniPhysics for Complex Systems, Department of Physics, University of Turin, Italy.
Thais S SabedotDepartment of Genetics Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, São Paulo, Brazil Center for Integrative Systems Biology - CISBi, NAP/USP, Ribeirão Preto, São Paulo, Brazil.
Tathiane M MaltaDepartment of Genetics Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, São Paulo, Brazil Center for Integrative Systems Biology - CISBi, NAP/USP, Ribeirão Preto, São Paulo, Brazil.
Stefano M PagnottaDepartment of Science and Technology, University of Sannio, Benevento, Italy Bioinformatics Laboratory, BIOGEM, Ariano Irpino, Avellino, Italy.
Isabella CastiglioniInstitute of Molecular Bioimaging and Physiology of the National Research Council (IBFM-CNR), Milan, Italy.
Michele CeccarelliQatar Computing Research Institute (QCRI), HBKU, Doha, Qatar.
Gianluca BontempiInteruniversity Institute of Bioinformatics in Brussels (IB), Brussels, Belgium Machine Learning Group (MLG), Department d'Informatique, Université libre de Bruxelles (ULB), Brussels, Belgium gbonte@ulb.ac.be.
Houtan NoushmehrDepartment of Genetics Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, São Paulo, Brazil Center for Integrative Systems Biology - CISBi, NAP/USP, Ribeirão Preto, São Paulo, Brazil houtan@usp.br.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Databases, GeneticBiomarkers, TumorBRCA1 ProteinBRCA2 ProteinComputational BiologyData MiningDNA MethylationGenome, HumanGenomicsHumansNeoplasmsStatistics as TopicBiomarkers, TumorBRCA1 ProteinBRCA1 protein, humanBRCA2 ProteinBRCA2 protein, human

Identifiers

PMID26704973
PMCPMC4856967

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.