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

Autor(es):Mostrar menos -

Colaprico, Antonio ^{[1, 2]} ; Silva, Tiago C. ^{[3, 4]} ; Olsen, Catharina ^{[1, 2]} ; Garofano, Luciano ^{[5, 6]} ; Cava, Claudia ^[7] ; Garolini, Davide ^[8] ; Sabedot, Thais S. ^{[3, 4]} ; Malta, Tathiane M. ^{[3, 4]} ; Pagnotta, Stefano M. ^{[5, 9]} ; Castiglioni, Isabella ; Ceccarelli, Michele ^[10] ; Bontempi, Gianluca ^{[1, 2]} ; Noushmehr, Houtan ^{[3, 4]}

Afiliação do(s) autor(es)

^[1] Interuniv Inst Bioinformat Brussels, Brussels - Belgium

^[2] Univ Libre Bruxelles, Dept Informat, Machine Learning Grp, Brussels - Belgium

^[3] Univ Sao Paulo, Ribeirao Preto Med Sch, Dept Genet, Sao Paulo - Brazil

^[4] NAP USP, Ctr Integrat Syst Biol CISBi, Sao Paulo - Brazil

^[5] Univ Sannio, Dept Sci & Technol, Benevento - Italy

^[6] Unltd Software Srl, Naples - Italy

^[7] Natl Res Council IBFM CNR, Inst Mol Bioimaging & Physiol, Milan - Italy

^[8] Univ Turin, Dept Phys, Phys Complex Syst, I-10124 Turin - Italy

^[9] BIOGEM, Bioinformat Lab, Avellino - Italy

^[10] HBKU, Qatar Comp Res Inst, Doha - Qatar

• Tipo de documento: Artigo Científico
• Fonte: Nucleic Acids Research; v. 44, n. 8 MAY 5 2016.
• Citações Web of Science: 151

Resumo

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. (AU)

• Processo FAPESP: 15/02844-7 - Alterações epigenômicas aberrantes que são definidas por assinaturas genômicas distintas associadas a gliomas: métodos e desenvolvimento
• Beneficiário: Tiago Chedraoui Silva
• Modalidade de apoio: Bolsas no Brasil - Mestrado
• Processo FAPESP: 14/02245-3 - Identificação de assinaturas epigenômicas que definem regiões regulatórias ativas do genoma associadas à diferenciação mesenquimal a partir de células-tronco pluripotentes humanas
• Beneficiário: Tathiane Maistro Malta Pereira
• Modalidade de apoio: Bolsas no Brasil - Pós-Doutorado
• Processo FAPESP: 15/07925-5 - Softwares de código aberto contendo ferramentas estatísticas para análise e integração de conjuntos de dados epigenômicos produzidos em alta escala, a fim de decifrar e entender redes reguladoras de câncer
• Beneficiário: Houtan Noushmehr
• Modalidade de apoio: Auxílio à Pesquisa - Jovens Pesquisadores