{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T20:34:31Z","timestamp":1772138071330,"version":"3.50.1"},"reference-count":45,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2025,2,6]],"date-time":"2025-02-06T00:00:00Z","timestamp":1738800000000},"content-version":"vor","delay-in-days":5,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Medical Research Council Fellowship","award":["MR\/W021455\/1"],"award-info":[{"award-number":["MR\/W021455\/1"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,2,4]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Motivation<\/jats:title>\n                    <jats:p>High-throughput omics technologies have revolutionized the identification of associations between individual traits and underlying biological characteristics, but still use \u2018one effect-size fits all\u2019 approaches. While covariates are often used, their potential as effect modifiers often remains unexplored.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>We propose ESPClust, a novel unsupervised method designed to identify covariates that modify the effect size of associations between sets of omics variables and outcomes. By extending the concept of moderators to encompass multiple exposures, ESPClust analyses the effect size profile (ESP) to identify regions in covariate space with different ESP, enabling the discovery of subpopulations with distinct associations. Applying ESPClust to synthetic data, insulin resistance and COVID-19 symptom manifestation, we demonstrate its versatility and ability to uncover nuanced effect size modifications that traditional analyses may overlook. By integrating information from multiple exposures, ESPClust identifies effect size modifiers in datasets that are too small for traditional univariate stratified analyses. This method provides a robust framework for understanding complex omics data and holds promise for personalised medicine.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>The source code ESPClust is available at https:\/\/github.com\/fjpreche\/ESPClust.git. It can be installed via Python package repositories as \u2018pip install ESPClust==1.1.0\u2019.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btaf065","type":"journal-article","created":{"date-parts":[[2025,2,6]],"date-time":"2025-02-06T13:23:36Z","timestamp":1738848216000},"source":"Crossref","is-referenced-by-count":0,"title":["ESPClust: unsupervised identification of modifiers for the effect size profile in omics association studies"],"prefix":"10.1093","volume":"41","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5663-5249","authenticated-orcid":false,"given":"Francisco J","family":"P\u00e9rez-Reche","sequence":"first","affiliation":[{"name":"School of Natural and Computing Sciences, University of Aberdeen , Aberdeen AB24 3UE,","place":["United Kingdom"]},{"name":"Department of Twin Research and Genetic Epidemiology, School of Life Course & Population Sciences, King\u2019s College London , London SE1 7EH,","place":["United Kingdom"]}]},{"given":"Nathan J","family":"Cheetham","sequence":"additional","affiliation":[{"name":"Department of Twin Research and Genetic Epidemiology, School of Life Course & Population Sciences, King\u2019s College London , London SE1 7EH,","place":["United Kingdom"]}]},{"given":"Ruth C E","family":"Bowyer","sequence":"additional","affiliation":[{"name":"Department of Twin Research and Genetic Epidemiology, School of Life Course & Population Sciences, King\u2019s College London , London SE1 7EH,","place":["United Kingdom"]},{"name":"The Alan Turing Institute , British Library , London NW1 2DB,","place":["United Kingdom"]}]},{"given":"Ellen J","family":"Thompson","sequence":"additional","affiliation":[{"name":"School of Psychology, Faculty of Science, Engineering and Medicine, University of Sussex , Brighton BN1 9QH,","place":["United Kingdom"]}]},{"given":"Francesca","family":"Tettamanzi","sequence":"additional","affiliation":[{"name":"Department of Twin Research and Genetic 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