Multiple-sequence functional annotation and the generalized hidden Markov phylogeny
Multiple-sequence functional annotation and the generalized hidden Markov phylogeny
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DOI：
10.1093/bioinformatics/bth153
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发表时间：
2004-08-12
期刊：
影响因子：
5.8
通讯作者：
Jordan, MI
中科院分区：
文献类型：
--
作者：
McAuliffe, JD;Pachter, L;Jordan, MI
动机：系统发育阴影是一种比较基因组学原理，允许从多个密切相关的生物体的序列中发现保守区域。我们开发了一个形式化的概率框架，将系统发育阴影与基于特征的功能注释方法相结合。由此产生的模型，一个广义隐马尔可夫系统发育（GHMP），适用于从进化约束中推断功能区域的各种情况。结果：我们展示了GHMPs如何用于预测多个灵长类动物序列中的完整共享基因结构。我们还描述了阴影，我们实现了这样一个预测系统。我们发现，在不同外显子区域的小样本上，shadow优于先前报道的从头开始基因发现器，包括比较人鼠方法。最后，我们报告了对阴影器性能的实证分析，该分析表明，只要五个精心选择的物种就足以在外显子划分中获得最大的灵敏度和特异性。
Motivation: Phylogenetic shadowing is a comparative genomics principle that allows for the discovery of conserved regions in sequences from multiple closely related organisms. We develop a formal probabilistic framework for combining phylogenetic shadowing with feature-based functional annotation methods. The resulting model, a generalized hidden Markov phylogeny (GHMP), applies to a variety of situations where functional regions are to be inferred from evolutionary constraints.Results: We show how GHMPs can be used to predict complete shared gene structures in multiple primate sequences. We also describe shadower, our implementation of such a prediction system. We find that shadower outperforms previously reported ab initio gene finders, including comparative human-mouse approaches, on a small sample of diverse exonic regions. Finally, we report on an empirical analysis of shadower's performance which reveals that as few as five well-chosen species may suffice to attain maximal sensitivity and specificity in exon demarcation.