{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,9]],"date-time":"2026-06-09T22:19:35Z","timestamp":1781043575173,"version":"3.54.1"},"reference-count":75,"publisher":"Oxford University Press (OUP)","issue":"6","license":[{"start":{"date-parts":[[2024,10,14]],"date-time":"2024-10-14T00:00:00Z","timestamp":1728864000000},"content-version":"vor","delay-in-days":21,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Ministry of Education, Singapore Tier 1 and SUG","award":["RS08\/21"],"award-info":[{"award-number":["RS08\/21"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,9,23]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Batch effects introduce significant variability into high-dimensional data, complicating accurate analysis and leading to potentially misleading conclusions if not adequately addressed. Despite technological and algorithmic advancements in biomedical research, effectively managing batch effects remains a complex challenge requiring comprehensive considerations. This paper underscores the necessity of a flexible and holistic approach for selecting batch effect correction algorithms (BECAs), advocating for proper BECA evaluations and consideration of artificial intelligence\u2013based strategies. We also discuss key challenges in batch effect correction, including the importance of uncovering hidden batch factors and understanding the impact of design imbalance, missing values, and aggressive correction. Our aim is to provide researchers with a robust framework for effective batch effects management and enhancing the reliability of high-dimensional data analyses.<\/jats:p>","DOI":"10.1093\/bib\/bbae515","type":"journal-article","created":{"date-parts":[[2024,10,14]],"date-time":"2024-10-14T06:07:11Z","timestamp":1728886031000},"source":"Crossref","is-referenced-by-count":20,"title":["Thinking points for effective batch correction on biomedical data"],"prefix":"10.1093","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5345-3535","authenticated-orcid":false,"given":"Harvard Wai Hann","family":"Hui","sequence":"first","affiliation":[{"name":"Lee Kong Chian School of Medicine, Nanyang Technological University , 59 Nanyang Drive, Singapore 636921,","place":["Singapore"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-0307-6214","authenticated-orcid":false,"given":"Weijia","family":"Kong","sequence":"additional","affiliation":[{"name":"Lee Kong Chian School of Medicine, Nanyang Technological University , 59 Nanyang Drive, Singapore 636921,","place":["Singapore"]},{"name":"School of Biological Sciences, Nanyang Technological University , 60 Nanyang Drive, Singapore 637551,","place":["Singapore"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wilson Wen Bin","family":"Goh","sequence":"additional","affiliation":[{"name":"Lee Kong Chian School of Medicine, Nanyang Technological University , 59 Nanyang Drive, Singapore 636921,","place":["Singapore"]},{"name":"School of Biological Sciences, Nanyang Technological University , 60 Nanyang Drive, Singapore 637551,","place":["Singapore"]},{"name":"Center for Biomedical Informatics, Nanyang Technological University , 59 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