Computational Methods to determine Epistatic Effects

汉龙0073785 研究者设计了有效的算法来识别导致复杂数量表型的上位效应。 该算法适用于数据集，对于样本中的每个个体，在固定的一组标记沿着与定量性状的值一起识别等位基因。 该算法寻求一个最佳的适合的表型作为一个总和的寄生效应。 该方法是在所有可能的效应组合的空间中重复搜索最佳拟合。 搜索利用随机漫步爬山技术。 这些爬山是自适应的，因为在随机行走中控制步骤选择的某些参数会根据先前行走的结果而演变。 人们普遍认为，大多数感兴趣的数量性状的遗传成分（例如，血压，身高）涉及许多基因之间的相互作用。 因此，推断数量性状遗传基础的计算方法必须包括上位效应的分析，即，在两个或多个遗传标记上选择等位基因以不同于单个等位基因效应总和的方式影响数量性状的情况。 在这个项目中，研究者开发了计算方法来识别这些上位效应，通过在可能的效应空间中进行重复搜索，寻找能够解释显著数量的性状变异的效应，这些搜索是自我教育，在这个意义上，后来的搜索从以前的搜索中学习. 随着搜索次数的增加，自适应机制将搜索集中在特别强的上位效应上。

Hanlon0073785 The investigator designs effective algorithms to identifyepistatic effects that contribute to a complex quantitativephenotype. The algorithms apply to datasets that, for eachindividual in a sample, identifies alleles at a fixed set ofmarkers along with the value of the quanitative trait. Thealgorithms seek an optimum fit for the phenotype as a sum ofepistatic effects. The approach is to perform repeated searchesfor an optimum fit in the space of all possible combinations ofeffects. The search utilizes random walk hill-climbingtechniques. These hill-climbs are adaptive in the sense thatcertain parameters, which control the choice of steps in therandom walks, evolve based on the outcomes of previous walks. It is widely accepted that the genetic components of mostinteresting quantitative traits (eg. blood pressure, height)involve interactions between many genes. So, computationalmethods to infer the genetic basis of quantitative traits mustinclude an analysis of epistatic effects, i.e., instances wherethe choice of allele at two or more genetic markers influencesthe value of the quantitative trait in ways that are differentfrom the sum of the effects of the individual alleles. In thisproject the investigator develops computational methods toidentify these epistatic effects by a process of doing repeatedsearches through the space of possible effects looking for onesthat explain a significant amount of the variation of the trait.These searches are self-educating in the sense that latersearches learn from earlier searches. As the number of searchesincreases, the adaptive mechanism focuses the search onparticularly strong epistatic effects.