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MATHEMATICAL ANALYSIS FOR THE ESTIMATION OF CHANGES IN THE LEVEL OF GENE EXPRESSION

机译:估算基因表达水平变化的数学分析

摘要

The present invention relates to a highly accurate and reproducible mathematically-based methodology for quantifying the levels of differential gene expression from microassay protocols. Specifically, the present invention provides a simple deductive approach, grounded in a Bayesian framework, to circumvent the heuristic-based limitation of previous methodologies. Rather than seeking a point-estimate of the fold-change of the level of gene expression, the present invention utilizes the derivation of mathematical formula to determine the a posteriori distribution of all the fold-changes of differential gene expression which may be inferred from the given measurements. From this a posteriori distribution the following information may be obtained: (i) an estimator for the fold-change of the level of gene expression; (ii) confidence limits for the fold-change, at any given confidence level; and (iii) a P-value for assessing the statistical significance of change. The present invention also possesses the advantage that fold-change estimates and confidence limits may even be assigned to signal pairs where both signals are zero or negative, without resorting to heuristic thresholds.
机译:本发明涉及一种高度精确和可重现的基于数学的方法,用于定量来自微量测定方案的差异基因表达水平。具体地,本发明提供了基于贝叶斯框架的简单推论方法,以规避先前方法的基于启发式的限制。本发明不是寻找基因表达水平的倍数变化的点估计,而是利用数学公式的推导来确定差异基因表达的所有倍数变化的后验分布,该后验分布可以从基因表达水平推断出。给定尺寸。从这种后验分布中,可以获得以下信息:(i)基因表达水平的倍数变化的估计子; (ii)在任何给定的置信水平下,倍数变化的置信限度; (iii)一个P值,用于评估变化的统计显着性。本发明还具有以下优点:甚至可以将倍数变化估计和置信极限分配给两个信号均为零或负的信号对,而无需借助启发式阈值。

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