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Practical Issues in Building Risk-Predicting Models for Complex Diseases

机译:建立复杂疾病风险预测模型的实际问题

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Recent genome-wide association studies have identified many genetic variants affecting complex human diseases. It is of great interest to build disease risk prediction models based on these data. In this article, we first discuss statistical challenges in using genome-wide association data for risk predictions, and then review the findings from the literature on this topic. We also demonstrate the performance of different methods through both simulation studies and application to real-world data.View full textDownload full textKey WordsComplex traits, Genome-wide association studies, High-dimensional data, Risk prediction, Single-nucleotide polymorphismRelated var addthis_config = { ui_cobrand: "Taylor & Francis Online", services_compact: "citeulike,netvibes,twitter,technorati,delicious,linkedin,facebook,stumbleupon,digg,google,more", pubid: "ra-4dff56cd6bb1830b" }; Add to shortlist Link Permalink http://dx.doi.org/10.1080/10543400903572829
机译:最近的全基因组关联研究已经确定了许多影响复杂人类疾病的遗传变异。基于这些数据建立疾病风险预测模型非常重要。在本文中,我们首先讨论了使用全基因组关联数据进行风险预测的统计挑战,然后回顾了有关该主题的文献中的发现。我们还通过仿真研究和将其应用于现实世界数据来证明不同方法的性能。查看全文下载全文关键词复杂性状,全基因组关联研究,高维数据,风险预测,单核苷酸多态性相关var addthis_config = { ui_cobrand:“ Taylor&Francis Online”,service_compact:“ citeulike,netvibes,twitter,technorati,delicious,linkedin,facebook,stumbleupon,digg,google,更多”,发布:“ ra-4dff56cd6bb1830b”};添加到候选列表链接永久链接http://dx.doi.org/10.1080/10543400903572829

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