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Interpretation of biological experiments changes with evolution of the Gene Ontology and its annotations.
Tomczak, Aurelie; Mortensen, Jonathan M; Winnenburg, Rainer; Liu, Charles; Alessi, Dominique T; Swamy, Varsha; Vallania, Francesco; Lofgren, Shane; Haynes, Winston; Shah, Nigam H; Musen, Mark A; Khatri, Purvesh.
Afiliação
  • Tomczak A; Stanford Institute for Immunity, Transplantation and Infection (ITI), Stanford University, Stanford, CA, 94305, USA.
  • Mortensen JM; Stanford Center for Biomedical Informatics Research (BMIR), Department of Medicine, Stanford University, Stanford, CA, 94305, USA.
  • Winnenburg R; Stanford Center for Biomedical Informatics Research (BMIR), Department of Medicine, Stanford University, Stanford, CA, 94305, USA.
  • Liu C; Stanford Center for Biomedical Informatics Research (BMIR), Department of Medicine, Stanford University, Stanford, CA, 94305, USA.
  • Alessi DT; Stanford Institute for Immunity, Transplantation and Infection (ITI), Stanford University, Stanford, CA, 94305, USA.
  • Swamy V; Stanford Center for Biomedical Informatics Research (BMIR), Department of Medicine, Stanford University, Stanford, CA, 94305, USA.
  • Vallania F; Stanford Institute for Immunity, Transplantation and Infection (ITI), Stanford University, Stanford, CA, 94305, USA.
  • Lofgren S; Stanford Institute for Immunity, Transplantation and Infection (ITI), Stanford University, Stanford, CA, 94305, USA.
  • Haynes W; Stanford Institute for Immunity, Transplantation and Infection (ITI), Stanford University, Stanford, CA, 94305, USA.
  • Shah NH; Stanford Institute for Immunity, Transplantation and Infection (ITI), Stanford University, Stanford, CA, 94305, USA.
  • Musen MA; Stanford Center for Biomedical Informatics Research (BMIR), Department of Medicine, Stanford University, Stanford, CA, 94305, USA.
  • Khatri P; Stanford Center for Biomedical Informatics Research (BMIR), Department of Medicine, Stanford University, Stanford, CA, 94305, USA.
Sci Rep ; 8(1): 5115, 2018 03 23.
Article em En | MEDLINE | ID: mdl-29572502
ABSTRACT
Gene Ontology (GO) enrichment analysis is ubiquitously used for interpreting high throughput molecular data and generating hypotheses about underlying biological phenomena of experiments. However, the two building blocks of this analysis - the ontology and the annotations - evolve rapidly. We used gene signatures derived from 104 disease analyses to systematically evaluate how enrichment analysis results were affected by evolution of the GO over a decade. We found low consistency between enrichment analyses results obtained with early and more recent GO versions. Furthermore, there continues to be a strong annotation bias in the GO annotations where 58% of the annotations are for 16% of the human genes. Our analysis suggests that GO evolution may have affected the interpretation and possibly reproducibility of experiments over time. Hence, researchers must exercise caution when interpreting GO enrichment analyses and should reexamine previous analyses with the most recent GO version.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Evolução Molecular / Biologia Computacional / Bases de Dados Genéticas / Anotação de Sequência Molecular / Ontologia Genética / Modelos Genéticos Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Sci Rep Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Evolução Molecular / Biologia Computacional / Bases de Dados Genéticas / Anotação de Sequência Molecular / Ontologia Genética / Modelos Genéticos Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Sci Rep Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Estados Unidos