{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T17:51:06Z","timestamp":1775757066078,"version":"3.50.1"},"reference-count":59,"publisher":"Oxford University Press (OUP)","issue":"11","license":[{"start":{"date-parts":[[2022,4,23]],"date-time":"2022-04-23T00:00:00Z","timestamp":1650672000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"name":"Korea Health Technology R&D Project through the Korea Health Industry Development Institute"},{"name":"Ministry of Health & Welfare, Republic of Korea","award":["HI16C2037"],"award-info":[{"award-number":["HI16C2037"]}]},{"name":"Bio-Synergy Research Project of the Ministry of Science, ICT and Future Planning through the National Research Foundation","award":["2013M3A9C4078158"],"award-info":[{"award-number":["2013M3A9C4078158"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,5,26]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Motivation<\/jats:title><jats:p>Pathway analyses have led to more insight into the underlying biological functions related to the phenotype of interest in various types of omics data. Pathway-based statistical approaches have been actively developed, but most of them do not consider correlations among pathways. Because it is well known that there are quite a few biomarkers that overlap between pathways, these approaches may provide misleading results. In addition, most pathway-based approaches tend to assume that biomarkers within a pathway have linear associations with the phenotype of interest, even though the relationships are more complex.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>To model complex effects including non-linear effects, we propose a new approach, Hierarchical structural CoMponent analysis using Kernel (HisCoM-Kernel). The proposed method models non-linear associations between biomarkers and phenotype by extending the kernel machine regression and analyzes entire pathways simultaneously by using the biomarker-pathway hierarchical structure. HisCoM-Kernel is a flexible model that can be applied to various omics data. It was successfully applied to three omics datasets generated by different technologies. Our simulation studies showed that HisCoM-Kernel provided higher statistical power than other existing pathway-based methods in all datasets. The application of HisCoM-Kernel to three types of omics dataset showed its superior performance compared to existing methods in identifying more biologically meaningful pathways, including those reported in previous studies.<\/jats:p><\/jats:sec><jats:sec><jats:title>Availability and implementation<\/jats:title><jats:p>The HisCoM-Kernel software is freely available at http:\/\/statgen.snu.ac.kr\/software\/HisCom-Kernel\/. The RNA-seq data underlying this article are available at https:\/\/xena.ucsc.edu\/, and the others will be shared on reasonable request to the corresponding author.<\/jats:p><\/jats:sec><jats:sec><jats:title>Supplementary information<\/jats:title><jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p><\/jats:sec>","DOI":"10.1093\/bioinformatics\/btac276","type":"journal-article","created":{"date-parts":[[2022,4,20]],"date-time":"2022-04-20T11:17:29Z","timestamp":1650453449000},"page":"3078-3086","source":"Crossref","is-referenced-by-count":7,"title":["Kernel-based hierarchical structural component models for pathway analysis"],"prefix":"10.1093","volume":"38","author":[{"given":"Suhyun","family":"Hwangbo","sequence":"first","affiliation":[{"name":"Interdisciplinary Program in Bioinformatics, Seoul National University , Seoul 151-747, Korea"},{"name":"Department of Genomic Medicine, Seoul National University Hospital , Seoul 03080, Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3458-1440","authenticated-orcid":false,"given":"Sungyoung","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Genomic Medicine, Seoul National University Hospital , Seoul 03080, Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7941-8933","authenticated-orcid":false,"given":"Seungyeoun","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Mathematics and Statistics, Sejong University , Sejong 05006, Korea"}]},{"given":"Heungsun","family":"Hwang","sequence":"additional","affiliation":[{"name":"Department of Psychology, McGill University , Montreal, QC H3A 1B1, Canada"}]},{"given":"Inyoung","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Statistics, Virginia Tech. , Blacksburg, VA 24060, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8294-590X","authenticated-orcid":false,"given":"Taesung","family":"Park","sequence":"additional","affiliation":[{"name":"Interdisciplinary Program in Bioinformatics, Seoul National University , Seoul 151-747, Korea"},{"name":"Department of Statistics, Seoul National University , Seoul 151-747, Korea"}]}],"member":"286","published-online":{"date-parts":[[2022,4,23]]},"reference":[{"key":"2023041403081066800_","doi-asserted-by":"crossref","first-page":"e1002358","DOI":"10.1371\/journal.pcbi.1002358","article-title":"Metabolic reconstruction for metagenomic data and its application to the human microbiome","volume":"8","author":"Abubucker","year":"2012","journal-title":"PLoS Comput. 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