利用基因组信息场理论（GIFT）分析基因型-表型关联
Analysis of Genotype-Phenotype Association using Genomic Informational Field Theory (GIFT)
摘要：
我们展示了如何场和信息理论可以用来量化基因型和表型的情况下，表型是一个连续变量之间的关系。给定一个样本人口的表型测量，从各种已知的基因型，我们展示了如何排序的表型数据可以导致量化的基因型的影响。该方法不假设数据具有高斯分布，它在提取基因型对表型的弱和不寻常的依赖性方面特别有效。然而，在数据具有特殊形式（例如高斯）的情况下，我们观察到有效表型字段具有特殊形式。我们使用渐近分析来解决这两个问题的正向和反向配方。我们展示了如何计算$p$ -值，以便可以量化表型和基因型之间的相关性的意义。这为全基因组关联研究GWAS中使用的传统方法提供了重要的概括。我们推导出一个场强，它可以用来推断基因型和表型之间的相关性，以及它们对表型分布的影响。
英文摘要：
We show how field- and information theory can be used to quantify the relationship between genotype and phenotype in cases where phenotype is a continuous variable. Given a sample population of phenotype measurements, from various known genotypes, we show how the ordering of phenotype data can lead to quantification of the effect of genotype. This method does not assume that the data has a Gaussian distribution, it is particularly effective at extracting weak and unusual dependencies of genotype on phenotype. However, in cases where data has a special form, (eg Gaussian), we observe that the effective phenotype field has a special form. We use asymptotic analysis to solve both the forward and reverse formulations of the problem. We show how $p$-values can be calculated so that the significance of correlation between phenotype and genotype can be quantified. This provides a significant generalisation of the traditional methods used in genome-wide association studies GWAS. We derive a field-strength which can be used to deduce how the correlations between genotype and phenotype, and their impact on the distribution of phenotypes.
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