{"title":"HCSeeker: A Classification Tool for Human Genetic Variant Hot and Cold Spots Designed for PM1 and Benign Criteria in the ACMG-AMP Guideline.","authors":"Xinpan Yuan, Xingquan Xia, Jinchen Li, Guihu Zhao","doi":"10.1016/j.gim.2025.101591","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>The PM1 criterion, which states that a variant is located in a mutational hot spot and/or critical and well-established functional domain without benign variation (such as the active site of an enzyme), is considered moderate evidence for assessing its pathogenicity. Although guidelines from the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) are widely adopted, the PM1 criterion remains limited from lacking a reliable database of variant hot spots. Compared to hot spots, cold spots are neglected by the guidelines. To improve variant classification, we suggest including cold spots for supporting benign classifications. Consequently , we have developed the HCSeeker to provide data support for PM1 and the 'Benign' criteria.</p><p><strong>Methods: </strong>HCSeeker employs the Kernel Density Estimation (KDE) and the Expectation-Maximization (EM) algorithm to identify hot and cold spot regions.</p><p><strong>Results: </strong>Through HCSeeker, we identified 988 hot spots and 682 cold spots across 889 genes and provided a public database (http://www.genemed.tech/hcseeker/) for researchers and clinicians to query variant locations, facilitating the application of ACMG/AMP PM1 or 'Benign' criteria.</p><p><strong>Conclusion: </strong>We developed the HCSeeker tool, which can effectively identify variant hot and cold spots within genes to enhancing the interpretability of gene variants.</p>","PeriodicalId":12717,"journal":{"name":"Genetics in Medicine","volume":" ","pages":"101591"},"PeriodicalIF":6.2000,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Genetics in Medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1016/j.gim.2025.101591","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
引用次数: 0
Abstract
Purpose: The PM1 criterion, which states that a variant is located in a mutational hot spot and/or critical and well-established functional domain without benign variation (such as the active site of an enzyme), is considered moderate evidence for assessing its pathogenicity. Although guidelines from the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) are widely adopted, the PM1 criterion remains limited from lacking a reliable database of variant hot spots. Compared to hot spots, cold spots are neglected by the guidelines. To improve variant classification, we suggest including cold spots for supporting benign classifications. Consequently , we have developed the HCSeeker to provide data support for PM1 and the 'Benign' criteria.
Methods: HCSeeker employs the Kernel Density Estimation (KDE) and the Expectation-Maximization (EM) algorithm to identify hot and cold spot regions.
Results: Through HCSeeker, we identified 988 hot spots and 682 cold spots across 889 genes and provided a public database (http://www.genemed.tech/hcseeker/) for researchers and clinicians to query variant locations, facilitating the application of ACMG/AMP PM1 or 'Benign' criteria.
Conclusion: We developed the HCSeeker tool, which can effectively identify variant hot and cold spots within genes to enhancing the interpretability of gene variants.
期刊介绍:
Genetics in Medicine (GIM) is the official journal of the American College of Medical Genetics and Genomics. The journal''s mission is to enhance the knowledge, understanding, and practice of medical genetics and genomics through publications in clinical and laboratory genetics and genomics, including ethical, legal, and social issues as well as public health.
GIM encourages research that combats racism, includes diverse populations and is written by authors from diverse and underrepresented backgrounds.