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Adjusting scoring matrices to correct overextended alignments

机译:调整评分矩阵以纠正过度延伸的比对

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Motivation: Sequence similarity searches performed with BLAST, SSEARCH and FASTA achieve high sensitivity by using scoring matrices (e. g. BLOSUM62) that target low identity (<33%) alignments. Although such scoring matrices can effectively identify distant homologs, they can also produce local alignments that extend beyond the homologous regions. Results: We measured local alignment start/stop boundary accuracy using a set of queries where the correct alignment boundaries were known, and found that 7% of BLASTP and 8% of SSEARCH alignment boundaries were overextended. Overextended alignments include non-homologous sequences; they occur most frequently between sequences that are more closely related (> 33% identity). Adjusting the scoring matrix to reflect the identity of the homologous sequence can correct higher identity overextended alignment boundaries. In addition, the scoring matrix that produced a correct alignment could be reliably predicted based on the sequence identity seen in the original BLOSUM62 alignment. Realigning with the predicted scoring matrix corrected 37% of all overextended alignments, resulting in more correct alignments than using BLOSUM62 alone.
机译:动机:通过使用针对低同一性(<33%)比对的得分矩阵(例如BLOSUM62),用BLAST,SSEARCH和FASTA进行的序列相似性搜索获得了高灵敏度。尽管这样的评分矩阵可以有效地识别远处的同源物,但是它们也可以产生超出同源区域的局部比对。结果:我们使用一组已知正确对齐边界的查询来测量局部对齐开始/停止边界的准确性,发现7%的BLASTP和8%的SSEARCH对齐边界被过度扩展。过度延伸的比对包括非同源序列;它们在相关性更高(> 33%同一性)的序列之间发生的频率最高。调整评分矩阵以反映同源序列的同一性可以纠正更高的同一性,过度延伸的比对边界。此外,可以基于原始BLOSUM62比对中看到的序列同一性,可靠地预测产生正确比对的得分矩阵。与预测的得分矩阵重新比对可纠正所有过度延伸比对的37%,比单独使用BLOSUM62可产生更多的比对。

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