The Challenge of Detecting Epistasis (G x G Interactions): Genetic Analysis Workshop 16
The Challenge of Detecting Epistasis (G x G Interactions): Genetic Analysis Workshop 16
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DOI：
10.1002/gepi.20474
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发表时间：
2009-01-01
影响因子：
2.1
通讯作者：
Province, Michael A.
中科院分区：
文献类型：
--
作者：
An, Ping;Mukherjee, Odity;Province, Michael A.
对上位性作为全基因组关联研究中未解释的变异的可能来源的兴趣正在增加。遗传分析研讨会16第9组的参与者评估了各种用于检测上位性的经典和新型分析方法，包括统计和机器学习范式，应用于真实和模拟数据。由于上位性的大小显然与外显率的大小有关，因此在某种程度上与模型框架的选择有关，因此在不同的建模框架下，一种模型下的强相互作用可能会最小化甚至完全消失，这并不奇怪。麝猫。植物学报，33（增刊1）：558 - 567,2009。(C) 2009 Wiley-Liss, Inc。
Interest is increasing in epistasis as a possible source of the unexplained variance missed by genome-wide association studies. The Genetic Analysis Workshop 16 Group 9 participants evaluated a wide variety of classical and novel analytical methods for detecting epistasis, in both the statistical and machine learning paradigms, applied to both real and simulated data. Because the magnitude of epistasis is clearly relative to scale of penetrance, and therefore to some extent, to the choice of model framework, it is not surprising that strong interactions under one model might be minimized or even disappear entirely under a different modeling framework. Genet. Epidetniol. 33 (Suppl. 1):S58-S67, 2009. (C) 2009 Wiley-Liss, Inc.