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首页> 外文会议>Asia-Pacific Bioinformatics Conference(APBC 2003); 200302; Adelaide(AU) >Inferring an Original Sequence from Erroneous Copies: a Bayesian Approach
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Inferring an Original Sequence from Erroneous Copies: a Bayesian Approach

机译：从错误的副本推断原始序列：贝叶斯方法

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摘要

This paper considers the problem of inferring an original sequence from a number of erroneous copies. The problem arises in DNA sequencing, particularly in the context of emerging technologies that provide high throughput or other advantages, but at the cost of introducing many errors. We develop a Bayesian probabilistic model of the introduction of errors, and search for a sequence that has maximum posterior probability with respect to the model. We present results of extensive tests in which error-prone sequencing of real DNA was simulated. The results obtained using the new approach are compared to results obtained by deriving a consensus sequence from a multiple sequence alignment. We find that a significant improvement in accuracy is obtained using the new approach. The implication is that high error levels need not be a barrier to the adoption of sequencing technologies that are in other respects promising, because most errors can be detected and corrected using a small number of reads.
机译：本文考虑了从多个错误副本中推断原始序列的问题。该问题出现在DNA测序中，特别是在提供高通量或其他优点但以引入许多错误为代价的新兴技术的背景下。我们开发了引入错误的贝叶斯概率模型，并搜索相对于模型具有最大后验概率的序列。我们介绍了对真实DNA易错测序进行模拟的广泛测试结果。将使用新方法获得的结果与通过从多序列比对中导出共有序列获得的结果进行比较。我们发现使用新方法可以显着提高准确性。言下之意是，高错误级别不一定会成为采用其他方面有前景的测序技术的障碍，因为大多数错误可以通过少量读取来检测和纠正。

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