School of Health and Related Research, University of Sheffield, Sheffield, United Kingdom.
PLoS One. 2011;6(12):e28636. doi: 10.1371/journal.pone.0028636. Epub 2011 Dec 13.
Genome wide association studies frequently reveal associations between disease susceptibility and polymorphisms outside coding regions. Such associations cannot always be explained by linkage disequilibrium with changes affecting the transcription products. This has stimulated the interest in characterising sequence variation influencing gene expression levels, in particular in changes acting in cis. Differences in transcription between the two alleles at an autosomal locus can be used to test the association between candidate polymorphisms and the modulation of gene expression in cis. This type of approach requires at least one transcribed polymorphism and one candidate polymorphism. In the past five years, different methods have been proposed to analyse such data. Here we use simulations and real data sets to compare the power of some of these methods. The results show that when it is not possible to determine the phase between the transcribed and potentially cis acting allele there is some advantage in using methods that estimate phased genotype and effect on expression simultaneously. However when the phase can be determined, simple regression models seem preferable because of their simplicity and flexibility. The simulations and the analysis of experimental data suggest that in the majority of situations, methods that assume a lognormal distribution of the allelic expression ratios are both robust to deviations from this assumption and more powerful than alternatives that do not make these assumptions.
全基因组关联研究经常揭示疾病易感性与编码区以外多态性之间的关联。这些关联不能总是用与改变转录产物有关的连锁不平衡来解释。这激发了人们对影响基因表达水平的序列变异特征的兴趣，特别是顺式作用的改变。常染色体基因座两个等位基因之间的转录差异可用于测试候选多态性与顺式基因表达调控之间的关联。这种方法需要至少一个转录多态性和一个候选多态性。在过去的五年中，已经提出了不同的方法来分析此类数据。在这里，我们使用模拟和真实数据集比较了其中一些方法的功效。结果表明，当无法确定转录和潜在顺式作用等位基因之间的相位时，使用同时估计有相位基因型和对表达影响的方法具有一定优势。然而，当相位可以确定时，由于其简单性和灵活性，简单回归模型似乎更可取。模拟和实验数据分析表明，在大多数情况下，假设等位基因表达比的对数正态分布的方法不仅对违反这些假设具有稳健性，而且比不做这些假设的替代方法更有效。
