Statistical distance between texts and filtration methods in sequence comparison

Abstract

Upon searching local similarities in long sequences, the necessity of a 'rapid' similarity search becomes acute. Quadratic complexity of dynamic programming algorithms forces the employment of filtration methods that allow elimination of the sequences with a low similarity level. The paper is devoted to the theoretical substantiations of the filtration method based on the statistical distance between texts. The notion of the filtration efficiency is introduced and the efficiency of several filters is estimated. It is shown that the efficiency of the statistical ltuple filtration upon DNA database search is associated with a potential extension of the original four-letter alphabet and grows exponentially with increasing I. The formula that allows one to estimate the filtration parameters is presented. 1991) are impractical for searching large databases, filtration methods (/-tuple analysis) for similarity search in the genetic databases were proposed in the pioneering papers of Wilbur and Lipman (1983) and Lipman and Pearson (1985) (for other filtration methods see Gusev et al.The filtration methods for fast similarity search are based on the simple observation that similar sequences share the same

Pervasive properties of the genomic signature

“…If the imprint of the global signature is locally pervasive, down to the scale of the single gene or coding sequence, large deviations on that scale could highlight segments introduced by recent horizontal transfer from another species [13]. So-called filtration methods, based on dissimilarity measures computed from dinucleotide counts, have been employed for the alignment-free computation of evolutionary distances between homologous sequences [14,15]. The "transition matrix method" was a similar technique involving raw counts of amino acid pairs in protein primary sequences [16].…”

Untitled

“…Current methods (reviewed in Pevzner, 1992) typically require two arbitrary assumptions to be made for each similarity search: one about the length of the longest common word that is to be considered and the other about the threshold of similarity for significant matches. The method proposed in this paper removes the need for any restrictions on word length while keeping the computation time linear, and it also provides a bound on significance, thus removing need for any arbitrary thresholds.…”

RAFTS3: Rapid Alignment-Free Tool for Sequence Similarity Search

“…Since then, it has been applied in phylogenetic reconstruction [8][9][10][11], identification of homologous proteins [4], genome annotation [12], classification of metagenomic sequences [13], and identification of regulatory sequences [14]. Also, it has been shown as an efficient technique for sequence filtering [15].…”