How should we measure proportionality on relative gene expression data?
How should we measure proportionality on relative gene expression data?
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DOI：
10.1007/s12064-015-0220-8
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发表时间：
2016-06
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通讯作者：
Notredame C
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文献类型：
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作者：
Erb I;Notredame C
相关性在基因表达分析中普遍使用，尽管其作为客观标准的有效性常常值得怀疑。如果没有反映细胞中原始 mRNA 计数的标准化可用，基因之间的相关性就会变得虚假。然而，使用称为对数比分析的相对分析方法可以绕过标准化的需要。这种方法可用于识别成比例的基因对，即由于对数比方差消失而可以从非标准化数据正确推断其相关性的基因对子集。为了解释非零对数比方差的大小，Lovell 等人最近提出了关于基因对一个成员的方差进行缩放的建议。在这里，我们分析推导出使用缩放时如何引入虚假比例。我们的分析基于对称比例系数（Lovell 等人简要提及），该系数比他们的统计有许多优势。我们详细展示了缩放所需参考的选择如何确定哪些基因对被识别为成比例的。我们证明，使用未改变的基因作为参考在灵敏度方面具有巨大的优势。我们还探讨了比例性和偏相关性之间的联系，并推导了部分比例系数的表达式。简短的数据分析部分将讨论的概念付诸实践。
Correlation is ubiquitously used in gene expression analysis although its validity as an objective criterion is often questionable. If no normalization reflecting the original mRNA counts in the cells is available, correlation between genes becomes spurious. Yet the need for normalization can be bypassed using a relative analysis approach called log-ratio analysis. This approach can be used to identify proportional gene pairs, i.e. a subset of pairs whose correlation can be inferred correctly from unnormalized data due to their vanishing log-ratio variance. To interpret the size of non-zero log-ratio variances, a proposal for a scaling with respect to the variance of one member of the gene pair was recently made by Lovell et al. Here we derive analytically how spurious proportionality is introduced when using a scaling. We base our analysis on a symmetric proportionality coefficient (briefly mentioned in Lovell et al.) that has a number of advantages over their statistic. We show in detail how the choice of reference needed for the scaling determines which gene pairs are identified as proportional. We demonstrate that using an unchanged gene as a reference has huge advantages in terms of sensitivity. We also explore the link between proportionality and partial correlation and derive expressions for a partial proportionality coefficient. A brief data-analysis part puts the discussed concepts into practice.