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Use of a Novel Nonparametric Version of DEPTH to Identify Genomic Regions Associated with Prostate Cancer Risk.

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作者单位: Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia. [1] Centre for Epidemiology and Biostatistics, University of Melbourne, Melbourne, Australia. [2] Human Genetics Foundation, Torino, Italy. [3] Université Paris-Saclay, Univ. Paris-Sud, UVSQ, CESP, INSERM, Villejuif, France. [4] Gustave Roussy, F-94805, Villejuif, France. [5] Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania. [6] IBM Research, Zurich, Switzerland. [7] UNU-MERIT (United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology), Maastricht University, Maastricht, the Netherlands. [8] Warsaw University of Technology, Warsaw, Poland. [9] School of Mathematics and Statistics, University of Melbourne, Parkville, Victoria, Australia. [10] IBM Research - Australia, Carlton, Australia. [11] Genetic Epidemiology Laboratory, Department of Pathology, University of Melbourne, Victoria, Australia. [12] Melbourne Bioinformatics Platform, Victorian Life Sciences Computation Initiative, University of Melbourne, Victoria, Australia. [13] Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom. [14] The Institute of Cancer Research, London, United Kingdom. [15] Centre for Epidemiology and Biostatistics, University of Melbourne, Melbourne, Australia. j.hopper@unimelb.edu.au. [16] Department of Epidemiology, School of Public Health and Institute of Health and Environment, Seoul National University, Seoul, South Korea. [17]
DOI 10.1158/1055-9965.EPI-16-0301
PMID 27539266
发布时间 2024-02-10
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Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology

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