☆ 4.7 Article

ipDMR: identification of differentially methylated regions with interval P-values

BIOINFORMATICS (2021)

期刊

BIOINFORMATICS

卷 37, 期 5, 页码 711-713

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OXFORD UNIV PRESS

DOI: 10.1093/bioinformatics/btaa732

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Biochemical Research Methods Biotechnology & Applied Microbiology Computer Science, Interdisciplinary Applications Mathematical & Computational Biology Statistics & Probability

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Intramural Research Program of the NIH, National Institute of Environmental Health Sciences [Z01 ES049033, Z01 ES049032, Z01 ES044005, P30ES00606]
NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES [ZIAES049032] Funding Source: NIH RePORTER

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ipDMR is an R software tool for identifying differentially methylated regions (DMRs) in epigenome-wide association analysis, which outperforms current methods with higher true positive rates and lower false discovery rates.

ipDMR is an R software tool for identification of differentially methylated regions (DMRs) using autocorrelated P-values for individual CpGs from epigenome-wide association analysis using array or bisulfite sequencing data. It summarizes P-values for adjacent CpGs, identifies association peaks and then extends peaks to find boundaries of DMRs. ipDMR uses BED format files as input and is easy to use. Simulations guided by real data found that ipDMR outperformed current available methods and provided slightly higher true positive rates and much lower false discovery rates.

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Evidence of Novel Susceptibility Variants for Prostate Cancer and a Multiancestry Polygenic Risk Score Associated with Aggressive Disease in Men of African Ancestry

Fei Chen, Ravi K. Madduri, Alex A. Rodriguez, Burcu F. Darst, Alisha Chou, Xin Sheng, Anqi Wang, Jiayi Shen, Edward J. Saunders, Suhn K. Rhie, Jeannette T. f Bensen, Sue A. Ingles, Rick A. Kittles, Sara S. Strom, Benjamin A. Rybicki, Barbara Nemesure, William B. Isaacs, Janet L. Stanford, Wei Zheng, Maureen Sanderson, Esther M. John, Jong Y. Park, Jianfeng Xu, Ying Wang, Sonja I. Berndt, Chad D. Huff, Edward D. Yeboah, Yao Tettey, Joseph Lachance, Wei Tang, Christopher T. Rentsch, Kelly Cho, Benjamin H. Mcmahon, Richard B. Biritwum, Andrew A. Adjei, Evelyn Tay, Ann Truelove, Shelley Niwa, Thomas A. Sellers, Kosj Yamoah, Adam B. Murphy, Dana C. Crawford, Alpa V. Patel, William S. Bush, Melinda C. Aldrich, Olivier Cussenot, Gyorgy Petrovics, Jennifer Cullen, Christine M. Neslund-Dudas, Mariana C. Stern, Zsofia Kote-Jarai, Koveela Govindasami, Michael B. Cook, Anand P. Chokkalingam, Ann W. Hsing, Phyllis J. Goodman, Thomas J. Hoffmann, Bettina F. Drake, Jennifer J. Hu, Jacob M. Keaton, Jacklyn N. Hellwege, Peter E. Clark, Mohamed Jalloh, Serigne M. Gueye, Lamine Niang, Olufemi Ogunbiyi, Michael O. Idowu, Olufemi Popoola, Akindele O. Adebiyi, Oseremen I. Aisuodionoe-Shadrach, Hafees O. Ajibola, Mustapha A. Jamda, Olabode P. Oluwole, Maxwell Nwegbu, Ben Adusei, Sunny Mante, Afua Darkwa-Abrahams, James E. Mensah, Halimatou Diop, Stephen K. Van Den Eeden, Pascal Blanchet, Jay H. Fowke, Graham Casey, Anselm J. Hennis, Alexander Lubwama, Ian M. Thompson, Robin Leach, Douglas F. Easton, Michael H. Preuss, Ruth J. Loos, Susan M. Gundell, Peggy Wan, James L. Mohler, Elizabeth T. Fontham, Gary J. Smith, Jack A. Taylor, Shiv Srivastava, Rosaline A. Eeles, John D. Carpten, Adam S. Kibel, Luc Multigner, Marie-Elise Parent, Florence Menegaux, Geraldine Cancel-Tassin, Eric A. Klein, Caroline Andrews, Timothy R. Rebbeck, Laurent Brureau, Stefan Ambs, Todd L. Edwards, Stephen Watya, Stephen J. Chanock, John S. Witte, William J. Blot, J. Michael Gaziano, Amy C. Justice, David Conti, Christopher A. Haiman

Summary: In this study, a large-scale genetic analysis was conducted in men of African ancestry, leading to the discovery of nine novel risk variants for prostate cancer (PCa). Furthermore, a multiancestry polygenic risk score was developed to effectively stratify PCa risk and differentiate the risk of aggressive and nonaggressive disease.

EUROPEAN UROLOGY (2023)

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Article Urology & Nephrology

Genome-wide Association Study of Bladder Cancer Reveals New Biological and Translational Insights

Stella Koutros, Lambertus A. Kiemeney, Parichoy Pal Choudhury, Roger L. Milne, Evangelina Lopez de Maturana, Yuanqing Ye, Vijai Joseph, Oscar Florez-Vargas, Lars Dyrskjot, Jonine Figueroa, Diptavo Dutta, Graham G. Giles, Michelle A. T. Hildebrandt, Kenneth Offit, Manolis Kogevinas, Elisabete Weiderpass, Marjorie L. McCullough, Neal D. Freedman, Demetrius Albanes, Charles Kooperberg, Victoria K. Cortessis, Margaret R. Karagas, Alison Johnson, Molly R. Schwenn, Dalsu Baris, Helena Furberg, Dean F. Bajorin, Olivier Cussenot, Geraldine Cancel-Tassin, Simone Benhamou, Peter Kraft, Stefano Porru, Angela Carta, Timothy Bishop, Melissa C. Southey, Giuseppe Matullo, Tony Fletcher, Rajiv Kumar, Jack A. Taylor, Philippe Lamy, Frederik Prip, Mark Kalisz, Stephanie J. Weinstein, Jan G. Hengstler, Silvia Selinski, Mark Harland, Mark Teo, Anne E. Kiltie, Adonina Tardon, Consol Serra, Alfredo Carrato, Reina Garcia-Closas, Josep Lloreta, Alan Schned, Petra Lenz, Elio Riboli, Paul Brennan, Anne Tjonneland, Thomas Otto, Daniel Ovsiannikov, Frank Volkert, Sita H. Vermeulen, K. K. Aben, Tessel E. Galesloot, Constance Turman, Immaculata De Vivo, Edward Giovannucci, David J. Hunter, Chancellor Hohensee, Rebecca Hunt, Alpa V. Patel, Wen-Yi Huang, Gudmar Thorleifsson, Manuela Gago-Dominguez, Pilar Amiano, Klaus Golka, Mariana C. Stern, Wusheng Yan, Jia Liu, Shengchao Alfred, Shilpa Katta, Amy Hutchinson, Belynda Hicks, William A. Wheeler, Mark P. Purdue, Katherine A. McGlynn, Cari M. Kitahara, Christopher A. Haiman, Mark H. Greene, Thorunn Rafnar, Nilanjan Chatterjee, Stephen J. Chanock, Xifeng Wu, Francisco X. Real, Debra T. Silverman, Montserrat Garcia-Closas, Kari Stefansson, Ludmila Prokunina-Olsson, Nuria Malats, Nathaniel Rothman

Summary: A meta-analysis of 32 studies identified novel genetic variants associated with bladder cancer risk and constructed a polygenic risk score (PRS) to stratify lifetime risk. These findings provide insights into the biological underpinnings of bladder cancer and have the potential to inform future preventive strategies.

EUROPEAN UROLOGY (2023)

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Article Oncology

Changes in methylation-based aging in women who do and do not develop breast cancer

Jacob K. Kresovich, Katie M. O'Brien, Zongli Xu, Clarice R. Weinberg, Dale P. Sandler, Jack A. Taylor

Summary: A study found that breast cancer survivors may experience faster biological aging. The diagnosis and treatment of breast cancer have an impact on biological aging, and different treatment methods have different effects.

JNCI-JOURNAL OF THE NATIONAL CANCER INSTITUTE (2023)

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