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TS-GOEA: a web tool for tissue-specific gene set enrichment analysis based on gene ontology.
Peng, Jiajie; Lu, Guilin; Xue, Hansheng; Wang, Tao; Shang, Xuequn.
Afiliação
  • Peng J; School of Computer Science, Northwestern Polytechnical University, Xi'an, 710129, China.
  • Lu G; School of Computer Science, Northwestern Polytechnical University, Xi'an, 710129, China.
  • Xue H; School of Computer Science, Northwestern Polytechnical University, Xi'an, 710129, China.
  • Wang T; School of Computer Science, Harbin Institute of Technology, Harbin, 150001, China.
  • Shang X; School of Computer Science, Northwestern Polytechnical University, Xi'an, 710129, China. shang@nwpu.edu.cn.
BMC Bioinformatics ; 20(Suppl 18): 572, 2019 Nov 25.
Article em En | MEDLINE | ID: mdl-31760951
ABSTRACT

BACKGROUND:

The Gene Ontology (GO) knowledgebase is the world's largest source of information on the functions of genes. Since the beginning of GO project, various tools have been developed to perform GO enrichment analysis experiments. GO enrichment analysis has become a commonly used method of gene function analysis. Existing GO enrichment analysis tools do not consider tissue-specific information, although this information is very important to current research.

RESULTS:

In this paper, we built an easy-to-use web tool called TS-GOEA that allows users to easily perform experiments based on tissue-specific GO enrichment analysis. TS-GOEA uses strict threshold statistical method for GO enrichment analysis, and provides statistical tests to improve the reliability of the analysis results. Meanwhile, TS-GOEA provides tools to compare different experimental results, which is convenient for users to compare the experimental results. To evaluate its performance, we tested the genes associated with platelet disease with TS-GOEA.

CONCLUSIONS:

TS-GOEA is an effective GO analysis tool with unique features. The experimental results show that our method has better performance and provides a useful supplement for the existing GO enrichment analysis tools. TS-GOEA is available at http//120.77.47.25678.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Transtornos Plaquetários / Biologia Computacional / Ontologia Genética Tipo de estudo: Evaluation_studies Limite: Humans Idioma: En Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Transtornos Plaquetários / Biologia Computacional / Ontologia Genética Tipo de estudo: Evaluation_studies Limite: Humans Idioma: En Ano de publicação: 2019 Tipo de documento: Article