TY - GEN

T1 - Pairwise statistical significance of local sequence alignment using substitution matrices with sequence-pair-specific distance

AU - Agrawal, Ankit

AU - Huang, Xiaoqiu

PY - 2008

Y1 - 2008

N2 - Pairwise sequence alignment forms the basis of numerous other applications in bioinformatics. The quality of an alignment is gauged by statistical significance rather than by alignment score alone. Therefore, accurate estimation of statistical significance of a pairwise alignment is an important problem in sequence comparison. Recently, it was shown that pairwise statistical significance does better in practice than database statistical significance, and also provides quicker individual pairwise estimates of statistical significance without having to perform time-consuming database search. Under an evolutionary model, a substitution matrix can be derived using a rate matrix and a fixed distance. Although the commonly used substitution matrices like BLOSUM62, etc. were not originally derived from a rate matrix under an evolutionary model, the corresponding rate matrices can be back calculated. Many researchers have derived different rate matrices using different methods and data. In this paper, we show that pairwise statistical significance using rate matrices with sequence-pair-specific distance performs significantly better compared to using a fixed distance. Pairwise statistical significance using sequence-pair-specific distanced substitution matrices also outperforms database statistical significance reported by BLAST.

AB - Pairwise sequence alignment forms the basis of numerous other applications in bioinformatics. The quality of an alignment is gauged by statistical significance rather than by alignment score alone. Therefore, accurate estimation of statistical significance of a pairwise alignment is an important problem in sequence comparison. Recently, it was shown that pairwise statistical significance does better in practice than database statistical significance, and also provides quicker individual pairwise estimates of statistical significance without having to perform time-consuming database search. Under an evolutionary model, a substitution matrix can be derived using a rate matrix and a fixed distance. Although the commonly used substitution matrices like BLOSUM62, etc. were not originally derived from a rate matrix under an evolutionary model, the corresponding rate matrices can be back calculated. Many researchers have derived different rate matrices using different methods and data. In this paper, we show that pairwise statistical significance using rate matrices with sequence-pair-specific distance performs significantly better compared to using a fixed distance. Pairwise statistical significance using sequence-pair-specific distanced substitution matrices also outperforms database statistical significance reported by BLAST.

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U2 - 10.1109/ICIT.2008.63

DO - 10.1109/ICIT.2008.63

M3 - Conference contribution

AN - SCOPUS:62449117842

SN - 9780769535135

T3 - Proceedings - 11th International Conference on Information Technology, ICIT 2008

SP - 94

EP - 99

BT - Proceedings - 11th International Conference on Information Technology, ICIT 2008

T2 - 11th International Conference on Information Technology, ICIT 2008

Y2 - 17 December 2008 through 20 December 2008

ER -