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Efficient and accurate P-value computation for Position Weight Matrices

机译:位置权重矩阵的高效准确的P值计算

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摘要

BackgroundPosition Weight Matrices (PWMs) are probabilistic representations of signals in sequences. They are widely used to model approximate patterns in DNA or in protein sequences. The usage of PWMs needs as a prerequisite to knowing the statistical significance of a word according to its score. This is done by defining the P-value of a score, which is the probability that the background model can achieve a score larger than or equal to the observed value. This gives rise to the following problem: Given a P-value, find the corresponding score threshold. Existing methods rely on dynamic programming or probability generating functions. For many examples of PWMs, they fail to give accurate results in a reasonable amount of time.
机译:背景位置权重矩阵(PWM)是序列中信号的概率表示。它们被广泛用于模拟DNA或蛋白质序列中的近似模式。使用PWM需要作为根据单词的分数了解单词的统计意义的前提。这是通过定义分数的P值完成的,P值是背景模型可以达到大于或等于观察值的分数的概率。这引起了以下问题:给定一个P值,找到相应的分数阈值。现有方法依赖于动态编程或概率生成功能。对于PWM的许多示例,它们无法在合理的时间内给出准确的结果。

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