论文标题
使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)
论文作者
论文摘要
我们展示了在表型是连续变量的情况下，如何使用场和信息理论来量化基因型和表型之间的关系。考虑到表型测量的样本群体，从各种已知的基因型中，我们展示了表型数据的排序如何导致基因型效应的量化。该方法不假定数据具有高斯分布，它在提取基因型对表型的弱且异常的依赖性方面特别有效。但是，在数据具有特殊形式（例如高斯）的情况下，我们观察到有效的表型场具有特殊的形式。我们使用渐近分析来解决问题的正向和逆向配方。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。这对全基因组关联研究GWAS中使用的传统方法进行了重大概括。我们得出了一个野外强度，可用于推断基因型和表型之间的相关性及其对表型分布的影响。
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.
