ULTRA: A Model Based Tool to Detect Tandem Repeats.

Daniel Olson, Travis Wheeler
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引用次数: 18

Abstract

In biological sequences, tandem repeats consist of tens to hundreds of residues of a repeated pattern, such as atgatgatgatgatg ('atg' repeated), often the result of replication slippage. Over time, these repeats decay so that the original sharp pattern of repetition is somewhat obscured, but even degenerate repeats pose a problem for sequence annotation: when two sequences both contain shared patterns of similar repetition, the result can be a false signal of sequence homology. We describe an implementation of a new hidden Markov model for detecting tandem repeats that shows substantially improved sensitivity to labeling decayed repetitive regions, presents low and reliable false annotation rates across a wide range of sequence composition, and produces scores that follow a stable distribution. On typical genomic sequence, the time and memory requirements of the resulting tool (ULTRA) are competitive with the most heavily used tool for repeat masking (TRF). ULTRA is released under an open source license and lays the groundwork for inclusion of the model in sequence alignment tools and annotation pipelines.

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ULTRA:一种基于模型的串联重复序列检测工具
在生物序列中,串联重复序列由数十到数百个重复模式的残基组成,例如atgatgatgatg ('atg'重复),通常是复制滑移的结果。随着时间的推移,这些重复会衰减,从而使原始的尖锐重复模式在某种程度上变得模糊,但即使是退化的重复也会给序列注释带来问题:当两个序列都包含相似重复的共享模式时,结果可能是序列同源性的错误信号。我们描述了一种用于检测串联重复序列的新隐马尔可夫模型的实现,该模型对标记衰减重复区域的灵敏度显着提高,在大范围的序列组成中呈现低而可靠的错误注释率,并产生遵循稳定分布的分数。在典型的基因组序列中,结果工具(ULTRA)的时间和内存要求与最常用的重复掩蔽工具(TRF)竞争。ULTRA是在开放源码许可下发布的,它为在序列比对工具和注释管道中包含模型奠定了基础。
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