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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....
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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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. |
format | Online Article Text |
id | pubmed-10009669 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
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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