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Integrated analysis of human DNA methylation, gene expression, and genomic variation in iMETHYL database using kernel tensor decomposition-based unsupervised feature extraction
Integrating gene expression, DNA methylation, and genomic variants simultaneously without location coincidence (i.e., irrespective of distance from each other) or pairwise coincidence (i.e., direct identification of triplets of gene expression, DNA methylation, and genomic variants, and not integrat...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10411815/ https://www.ncbi.nlm.nih.gov/pubmed/37556429 http://dx.doi.org/10.1371/journal.pone.0289029 |
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author | Taguchi, Y-h. Komaki, Shohei Sutoh, Yoichi Ohmomo, Hideki Otsuka-Yamasaki, Yayoi Shimizu, Atsushi |
author_facet | Taguchi, Y-h. Komaki, Shohei Sutoh, Yoichi Ohmomo, Hideki Otsuka-Yamasaki, Yayoi Shimizu, Atsushi |
author_sort | Taguchi, Y-h. |
collection | PubMed |
description | Integrating gene expression, DNA methylation, and genomic variants simultaneously without location coincidence (i.e., irrespective of distance from each other) or pairwise coincidence (i.e., direct identification of triplets of gene expression, DNA methylation, and genomic variants, and not integration of pairwise coincidences) is difficult. In this study, we integrated gene expression, DNA methylation, and genome variants from the iMETHYL database using the recently proposed kernel tensor decomposition-based unsupervised feature extraction method with limited computational resources (i.e., short CPU time and small memory requirements). Our methods do not require prior knowledge of the subjects because they are fully unsupervised in that unsupervised tensor decomposition is used. The selected genes and genomic variants were significantly targeted by transcription factors that were biologically enriched in KEGG pathway terms as well as in the intra-related regulatory network. The proposed method is promising for integrated analyses of gene expression, methylation, and genomic variants with limited computational resources. |
format | Online Article Text |
id | pubmed-10411815 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-104118152023-08-10 Integrated analysis of human DNA methylation, gene expression, and genomic variation in iMETHYL database using kernel tensor decomposition-based unsupervised feature extraction Taguchi, Y-h. Komaki, Shohei Sutoh, Yoichi Ohmomo, Hideki Otsuka-Yamasaki, Yayoi Shimizu, Atsushi PLoS One Research Article Integrating gene expression, DNA methylation, and genomic variants simultaneously without location coincidence (i.e., irrespective of distance from each other) or pairwise coincidence (i.e., direct identification of triplets of gene expression, DNA methylation, and genomic variants, and not integration of pairwise coincidences) is difficult. In this study, we integrated gene expression, DNA methylation, and genome variants from the iMETHYL database using the recently proposed kernel tensor decomposition-based unsupervised feature extraction method with limited computational resources (i.e., short CPU time and small memory requirements). Our methods do not require prior knowledge of the subjects because they are fully unsupervised in that unsupervised tensor decomposition is used. The selected genes and genomic variants were significantly targeted by transcription factors that were biologically enriched in KEGG pathway terms as well as in the intra-related regulatory network. The proposed method is promising for integrated analyses of gene expression, methylation, and genomic variants with limited computational resources. Public Library of Science 2023-08-09 /pmc/articles/PMC10411815/ /pubmed/37556429 http://dx.doi.org/10.1371/journal.pone.0289029 Text en © 2023 Taguchi et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Taguchi, Y-h. Komaki, Shohei Sutoh, Yoichi Ohmomo, Hideki Otsuka-Yamasaki, Yayoi Shimizu, Atsushi Integrated analysis of human DNA methylation, gene expression, and genomic variation in iMETHYL database using kernel tensor decomposition-based unsupervised feature extraction |
title | Integrated analysis of human DNA methylation, gene expression, and genomic variation in iMETHYL database using kernel tensor decomposition-based unsupervised feature extraction |
title_full | Integrated analysis of human DNA methylation, gene expression, and genomic variation in iMETHYL database using kernel tensor decomposition-based unsupervised feature extraction |
title_fullStr | Integrated analysis of human DNA methylation, gene expression, and genomic variation in iMETHYL database using kernel tensor decomposition-based unsupervised feature extraction |
title_full_unstemmed | Integrated analysis of human DNA methylation, gene expression, and genomic variation in iMETHYL database using kernel tensor decomposition-based unsupervised feature extraction |
title_short | Integrated analysis of human DNA methylation, gene expression, and genomic variation in iMETHYL database using kernel tensor decomposition-based unsupervised feature extraction |
title_sort | integrated analysis of human dna methylation, gene expression, and genomic variation in imethyl database using kernel tensor decomposition-based unsupervised feature extraction |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10411815/ https://www.ncbi.nlm.nih.gov/pubmed/37556429 http://dx.doi.org/10.1371/journal.pone.0289029 |
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