Pairagon: a highly accurate, HMM-based cDNA-to-genome aligner
Pairagon: a highly accurate, HMM-based cDNA-to-genome aligner
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DOI：
10.1093/bioinformatics/btp273
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发表时间：
2009-07-01
期刊：
影响因子：
5.8
通讯作者：
Brent, Michael R.
中科院分区：
文献类型：
--
作者：
Lu, David V.;Brown, Randall H.;Brent, Michael R.
动机：确定基因组中内含子-外显子结构的最准确方法是将剪接的cDNA序列与基因组进行比对。因此，cDNA到基因组比对程序是大多数注释管道的关键组成部分。用于选择最佳比对的评分系统是比对准确性的主要决定因素，而阻止考虑某些比对的算法是运行时间和内存使用的主要决定因素。准确性和速度都是重要的考虑因素，在选择一个比对算法，但评分系统已经收到了少得多的关注比questicistics.Results：我们目前Pairagon，一对隐马尔可夫模型为基础的cDNA到基因组比对程序，作为最准确的比对序列与高和低的身份水平。我们进行了一系列实验，测试不同序列同一性的比对准确度。我们首先通过拼接苍蝇和人类参考基因组序列中的外显子序列来创建“完美”的模拟cDNA序列。然后使用真实的突变模拟器将完整的参考基因组序列突变到不同程度，并使用Pairagon和12种其他比对器将完美的cDNA与它们进行比对。为了验证这些结果与自然序列，我们进行了跨物种比对，使用人，小鼠和大鼠的orthopathic成绩单。我们发现，对齐的准确性在很大程度上依赖于序列的同一性。对于具有100%同一性的序列，Pairagon实现了> 99.6%的准确度水平，具有任何其他比对器的四分之一的误差。此外，对于只有85%相同的人类/小鼠比对，Pairagon达到了87%的准确率，高于任何其他比对器。
Motivation: The most accurate way to determine the intron-exon structures in a genome is to align spliced cDNA sequences to the genome. Thus, cDNA-to-genome alignment programs are a key component of most annotation pipelines. The scoring system used to choose the best alignment is a primary determinant of alignment accuracy, while heuristics that prevent consideration of certain alignments are a primary determinant of runtime and memory usage. Both accuracy and speed are important considerations in choosing an alignment algorithm, but scoring systems have received much less attention than heuristics.Results: We present Pairagon, a pair hidden Markov model based cDNA-to-genome alignment program, as the most accurate aligner for sequences with high- and low-identity levels. We conducted a series of experiments testing alignment accuracy with varying sequence identity. We first created 'perfect' simulated cDNA sequences by splicing the sequences of exons in the reference genome sequences of fly and human. The complete reference genome sequences were then mutated to various degrees using a realistic mutation simulator and the perfect cDNAs were aligned to them using Pairagon and 12 other aligners. To validate these results with natural sequences, we performed cross-species alignment using orthologous transcripts from human, mouse and rat.We found that aligner accuracy is heavily dependent on sequence identity. For sequences with 100% identity, Pairagon achieved accuracy levels of > 99.6%, with one quarter of the errors of any other aligner. Furthermore, for human/mouse alignments, which are only 85% identical, Pairagon achieved 87% accuracy, higher than any other aligner.