ArticleBMC bioinformatics2019
TS-GOEA: a web tool for tissue-specific gene set enrichment analysis based on gene ontology.
Article in BMC bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Analysis of Pharmacological Activities and Mechanisms of Essential Oil in Flowers ofCurrent issues in molecular biology · 2025Article
- Histone-related gene WDR77 promotes tumor progression through cell cycle regulation in skin cutaneous melanoma.Frontiers in immunology · 2025Article
- Identification of DNA motif pairs on paired sequences based on composite heterogeneous graph.Frontiers in genetics · 2024Article
- A functional gene module identification algorithm in gene expression data based on genetic algorithm and gene ontology.BMC genomics · 2023Article
- Full-length transcriptome sequencing reveals the molecular mechanism of potato seedlings responding to low-temperature.BMC plant biology · 2022Article
- Comprehensive Analysis of the Effect of 20(Molecules (Basel, Switzerland) · 2022Article
- CKMT1A is a novel potential prognostic biomarker in patients with endometrial cancer.PloS one · 2022Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe 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.
resultsIn 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.
conclusionsTS-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://120.77.47.2:5678.
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