{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,13]],"date-time":"2026-01-13T09:42:58Z","timestamp":1768297378886,"version":"3.49.0"},"reference-count":31,"publisher":"Oxford University Press (OUP)","issue":"5","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2014,3,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Motivation: Advancements in high-throughput technology have allowed researchers to examine the genetic etiology of complex human traits in a robust fashion. Although genome-wide association studies have identified many novel variants associated with hundreds of traits, a large proportion of the estimated trait heritability remains unexplained. One hypothesis is that the commonly used statistical techniques and study designs are not robust to the complex etiology that may underlie these human traits. This etiology could include non-linear gene \u00d7 gene or gene \u00d7 environment interactions. Additionally, other levels of biological regulation may play a large role in trait variability.<\/jats:p><jats:p>Results: To address the need for computational tools that can explore enormous datasets to detect complex susceptibility models, we have developed a software package called the Analysis Tool for Heritable and Environmental Network Associations (ATHENA). ATHENA combines various variable filtering methods with machine learning techniques to analyze high-throughput categorical (i.e. single nucleotide polymorphisms) and quantitative (i.e. gene expression levels) predictor variables to generate multivariable models that predict either a categorical (i.e. disease status) or quantitative (i.e. cholesterol levels) outcomes. The goal of this article is to demonstrate the utility of ATHENA using simulated and biological datasets that consist of both single nucleotide polymorphisms and gene expression variables to identify complex prediction models. Importantly, this method is flexible and can be expanded to include other types of high-throughput data (i.e. RNA-seq data and biomarker measurements).<\/jats:p><jats:p>Availability: ATHENA is freely available for download. The software, user manual and tutorial can be downloaded from http:\/\/ritchielab.psu.edu\/ritchielab\/software.<\/jats:p><jats:p>Contact: \u00a0marylyn.ritchie@psu.edu<\/jats:p><jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btt572","type":"journal-article","created":{"date-parts":[[2013,10,23]],"date-time":"2013-10-23T01:14:23Z","timestamp":1382490863000},"page":"698-705","source":"Crossref","is-referenced-by-count":45,"title":["ATHENA: the analysis tool for heritable and environmental network associations"],"prefix":"10.1093","volume":"30","author":[{"given":"Emily R.","family":"Holzinger","sequence":"first","affiliation":[{"name":"1 Inherited Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, Baltimore, MD, USA and 2Department of Biochemistry and Molecular Biology, Center for Systems Genomics, Pennsylvania State University, University Park, PA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Scott M.","family":"Dudek","sequence":"additional","affiliation":[{"name":"1 Inherited Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, Baltimore, MD, USA and 2Department of Biochemistry and Molecular Biology, Center for Systems Genomics, Pennsylvania State University, University Park, PA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alex T.","family":"Frase","sequence":"additional","affiliation":[{"name":"1 Inherited Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, Baltimore, MD, USA and 2Department of Biochemistry and Molecular Biology, Center for Systems Genomics, Pennsylvania State University, University Park, PA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sarah A.","family":"Pendergrass","sequence":"additional","affiliation":[{"name":"1 Inherited Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, Baltimore, MD, USA and 2Department of Biochemistry and Molecular Biology, Center for Systems Genomics, Pennsylvania State University, University Park, PA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marylyn D.","family":"Ritchie","sequence":"additional","affiliation":[{"name":"1 Inherited Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, Baltimore, MD, USA and 2Department of Biochemistry and Molecular Biology, Center for Systems Genomics, Pennsylvania State University, University Park, PA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2013,10,21]]},"reference":[{"key":"2023012710425920900_btt572-B1","doi-asserted-by":"crossref","first-page":"1294","DOI":"10.1093\/bioinformatics\/btm108","article-title":"GenABEL: an R library for genome-wide association analysis","volume":"23","author":"Aulchenko","year":"2007","journal-title":"Bioinformatics"},{"key":"2023012710425920900_btt572-B2","doi-asserted-by":"crossref","DOI":"10.1093\/oso\/9780198538493.001.0001","volume-title":"Neural Networks for Pattern Recognition","author":"Bishop","year":"1995"},{"key":"2023012710425920900_btt572-B3","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random Forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Machine Learning"},{"key":"2023012710425920900_btt572-B4","first-page":"368","article-title":"Biofilter: a knowledge-integration system for the multi-locus analysis of genome-wide association studies","author":"Bush","year":"2009","journal-title":"Pac. 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