Searching for repeats, as an example of using the generalised Ruzzo-Tompa algorithm to find optimal subsequences with gaps

Abstract

Background Some biological sequences contain subsequences of unusual composition, e.g., some proteins contain DNA binding domains, transmembrane regions, and charged regions; and some DNA sequences contain repeats. Requiring time linear in the length of an input sequence, the Ruzzo-Tompa (RT) Algorithm finds subsequences of unusual composition, using a sequence of scores as input and the corresponding “maximal segments” as output. (Loosely, maximal segments are the contiguous subsequences having greatest total score.) Just as gaps improved the sensitivity of BLAST, in principle gaps could help tune other tools, to improve sensitivity when searching for subsequences of unusual composition. Results Call a graph whose vertices are totally ordered a “totally ordered graph”. In a totally ordered graph, call a path whose vertices are in increasing order an “increasing path”. The input of the RT Algorithm can be generalized to a finite, totally ordered, weighted graph, so the algorithm then locates maximal segments, corresponding to increasing paths of maximal weight. The generalization permits penalized deletion of unfavorable letters from contiguous subsequences, so the generalized Ruzzo-Tompa algorithm can find subsequences with greatest total gapped scores. The search for inexact simple repeats in DNA exemplifies some of the concepts. For some limited types of repeats, RepWords, a repeat-finding tool based on the principled use of the Ruzzo-Tompa algorithm, performed better than a similar extant tool. Conclusions With minimal programming effort, the generalization of the Ruzzo-Tompa algorithm given in this article could improve the performance of many programs for finding biological subsequences of unusual composition.

Most of the tight positional conservation of transcription factor binding sites near the transcription start site reflects their co-localization within regulatory modules

“…The Ruzzo-Tompa algorithm calculates maximal segments ( i ,  j ] [75]. The maximal segments, which satisfy S ( i , j ]  =  Ŝ j  > 0, yield contiguous alignment columns rich in motifs [76, 77]. (See Fig.…”

A New DNA sequencing alignment methodology using the Longest Common Subsequence technique

“…This filtering technique affords a considerable speed-up over CD-HIT without loss of sensitivity. Spouge J L, Mario-Ramrez L, Sheetlin SL [6] proposed the generalized Ruzzo-Tompa algorithm to find optimal subsequences with gaps in 2014 where the linear-time Ruzzo-Tompa (RT) algorithm finds subsequences of unusual composition, using a sequence of scores as input and the corresponding 'maximal segments' as output. Murugan and U. Udayakumar [7] proposed the sequence similarity between genetic codes using improved longest common subsequence algorithm in 2017.…”