通过贝叶斯假设检验对多序列比对进行质量评估。

Quality estimation of multiple sequence alignments by Bayesian hypothesis testing.

作者信息

Tomovic Andrija, Oakeley Edward J

机构信息

Friedrich Miescher Institute for Biomedical Research, Novartis Research Foundation, Maulbeerestrasse 66, CH-4056 Basel.

出版信息

Bioinformatics. 2007 Sep 15;23(18):2488-90. doi: 10.1093/bioinformatics/btm366. Epub 2007 Jul 27.

DOI:10.1093/bioinformatics/btm366

PMID:17660204

Abstract

UNLABELLED

In this work we present a web-based tool for estimating multiple alignment quality using Bayesian hypothesis testing. The proposed method is very simple, easily implemented and not time consuming with a linear complexity. We evaluated method against a series of different alignments (a set of random and biologically derived alignments) and compared the results with tools based on classical statistical methods (such as sFFT and csFFT). Taking correlation coefficient as an objective criterion of the true quality, we found that Bayesian hypothesis testing performed better on average than the classical methods we tested. This approach may be used independently or as a component of any tool in computational biology which is based on the statistical estimation of alignment quality.

AVAILABILITY

http://www.fmi.ch/groups/functional.genomics/tool.htm.

SUPPLEMENTARY INFORMATION

Supplementary data are available from http://www.fmi.ch/groups/functional.genomics/tool-Supp.htm.

摘要

未标注

在这项工作中，我们展示了一种基于网络的工具，用于使用贝叶斯假设检验来估计多序列比对质量。所提出的方法非常简单，易于实现，且具有线性复杂度，不耗时。我们针对一系列不同的比对（一组随机和生物学衍生的比对）评估了该方法，并将结果与基于经典统计方法的工具（如sFFT和csFFT）进行了比较。以相关系数作为真实质量的客观标准，我们发现贝叶斯假设检验平均而言比我们测试的经典方法表现更好。这种方法可以独立使用，也可以作为计算生物学中任何基于比对质量统计估计的工具的一个组件。