预测果蝇基因组调控区的统计薄尾检验
A statistical thin-tail test of predicting regulatory regions in the Drosophila genome
摘要：
背景资料：转录因子结合位点（TFBS）和顺式调控模块（CRMs）的识别是研究基因表达的关键步骤，但由于对特定相互作用的了解有限，试图区分CRMs和NCNRs的计算方法仍然是一个具有挑战性的问题。研究方法：顺式调控模块（CRM）的统计特性进行了探讨，通过估计的相似词集分布与过度代表（Z-得分）。据观察，标准物质往往具有薄尾Z分数分布。提出了一种新的具有两个稀疏系数的统计学薄尾检验来区分标准物质和非编码非调节区。结果如下：与现有的fluffy-tail检验相比，第一个稀疏系数的设计减少了计算时间，使得新的稀疏检验非常适合后基因组时代的长序列和大数据库分析;第二个稀疏系数的设计提高了标准物质和非标准物质之间的分离精度。这两个薄度系数可以作为有价值的筛选指标，预测标准物质的实验。结论：新的薄尾测试提供了一个高效和有效的手段，用于区分CRM从NCNRs的基础上的特定的统计特性的CRM，并可以指导未来的实验，旨在寻找新的CRM在后基因组时代。
英文摘要：
Background: The identification of transcription factor binding sites (TFBSs) and cis-regulatory modules (CRMs) is a crucial step in studying gene expression, but the computational method attempting to distinguish CRMs from NCNRs still remains a challenging problem due to the limited knowledge of specific interactions involved. Methods: The statistical properties of cis-regulatory modules (CRMs) are explored by estimating the similar-word set distribution with overrepresentation (Z-score). It is observed that CRMs tend to have a thin-tail Z-score distribution. A new statistical thin-tail test with two thinness coefficients is proposed to distinguish CRMs from non-coding non-regulatory regions (NCNRs). Results: As compared with the existing fluffy-tail test, the first thinness coefficient is designed to reduce computational time, making the novel thin-tail test very suitable for long sequences and large database analysis in the post-genome time and the second one to improve the separation accuracy between CRMs and NCNRs. These two thinness coefficients may serve as valuable filtering indexes to predict CRMs experimentally. Conclusions: The novel thin-tail test provides an efficient and effective means for distinguishing CRMs from NCNRs based on the specific statistical properties of CRMs and can guide future experiments aimed at finding new CRMs in the post-genome time.
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