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A gene pathway enrichment method based on improved TF-IDF algorithm

Gene pathway enrichment analysis is a widely used method to analyze whether a gene set is statistically enriched on certain biological pathway network. Current gene pathway enrichment methods commonly consider local importance of genes in pathways without considering the interactions between genes....

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Detalles Bibliográficos
Autores principales: Xu, Shutan, Leng, Yinhui, Feng, Guofu, Zhang, Chenjing, Chen, Ming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10009669/
https://www.ncbi.nlm.nih.gov/pubmed/36923007
http://dx.doi.org/10.1016/j.bbrep.2023.101421
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author Xu, Shutan
Leng, Yinhui
Feng, Guofu
Zhang, Chenjing
Chen, Ming
author_facet Xu, Shutan
Leng, Yinhui
Feng, Guofu
Zhang, Chenjing
Chen, Ming
author_sort Xu, Shutan
collection PubMed
description Gene pathway enrichment analysis is a widely used method to analyze whether a gene set is statistically enriched on certain biological pathway network. Current gene pathway enrichment methods commonly consider local importance of genes in pathways without considering the interactions between genes. In this paper, we propose a gene pathway enrichment method (GIGSEA) based on improved TF-IDF algorithm. This method employs gene interaction data to calculate the influence of genes based on the local importance in a pathway as well as the global specificity. Computational experiment result shows that, compared with traditional gene set enrichment analysis method, our proposed method in this paper can find more specific enriched pathways related to phenotype with higher efficiency.
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spelling pubmed-100096692023-03-14 A gene pathway enrichment method based on improved TF-IDF algorithm Xu, Shutan Leng, Yinhui Feng, Guofu Zhang, Chenjing Chen, Ming Biochem Biophys Rep Research Article Gene pathway enrichment analysis is a widely used method to analyze whether a gene set is statistically enriched on certain biological pathway network. Current gene pathway enrichment methods commonly consider local importance of genes in pathways without considering the interactions between genes. In this paper, we propose a gene pathway enrichment method (GIGSEA) based on improved TF-IDF algorithm. This method employs gene interaction data to calculate the influence of genes based on the local importance in a pathway as well as the global specificity. Computational experiment result shows that, compared with traditional gene set enrichment analysis method, our proposed method in this paper can find more specific enriched pathways related to phenotype with higher efficiency. Elsevier 2023-03-06 /pmc/articles/PMC10009669/ /pubmed/36923007 http://dx.doi.org/10.1016/j.bbrep.2023.101421 Text en © 2023 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Article
Xu, Shutan
Leng, Yinhui
Feng, Guofu
Zhang, Chenjing
Chen, Ming
A gene pathway enrichment method based on improved TF-IDF algorithm
title A gene pathway enrichment method based on improved TF-IDF algorithm
title_full A gene pathway enrichment method based on improved TF-IDF algorithm
title_fullStr A gene pathway enrichment method based on improved TF-IDF algorithm
title_full_unstemmed A gene pathway enrichment method based on improved TF-IDF algorithm
title_short A gene pathway enrichment method based on improved TF-IDF algorithm
title_sort gene pathway enrichment method based on improved tf-idf algorithm
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10009669/
https://www.ncbi.nlm.nih.gov/pubmed/36923007
http://dx.doi.org/10.1016/j.bbrep.2023.101421
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