A memory-efficient algorithm for multiple sequence alignment with constraints

Abstract

http://genome.life.nctu.edu.tw/MUSICME.

Constrained sequence alignment: A general model and the hardness results

“…The input sequences are in effect annotated with the substrings representing the candidate occurrences of each pattern. This generalizes the previous formulations since, given patterns defined in [20,6,21,16,2,7], the occurrences can be easily annotated in the sequences by well-established pattern matchers (e.g., the UNIX utility grep for regular expression patterns), thereby transforming the original patterns into an instance of our formulation. The formulation here also enables one to adopt mixed pattern definitions simultaneously in the analysis, for example some patterns can be specified by regular expressions and the others by strings with mismatch tolerance.…”

“…This formulation enables the user to align sequences so that known motifs specified in the constraint are required to be aligned together. Lu and Huang [16] then reduced the memory requirement of the algorithm in [21], which significantly improves the applicability of the tool. Arslan introduced the regular expression constrained sequence alignment (RECSA) problem [2], in which a constraint is a regular expression, and a feasible solution is an alignment containing a run of contiguous columns corresponding to two substrings, one for each input sequence, such that both substrings match the regular expression constraint.…”

“…To facilitate further discussion we say that in all these works a constraint is a sequence of patterns; a pattern is a simple character in [20,6], a substring allowing mismatches in [21,16] and a regular expression in [2,7]. Each pattern is described by its sequence content in these works.…”

“…The formulation here also enables one to adopt mixed pattern definitions simultaneously in the analysis, for example some patterns can be specified by regular expressions and the others by strings with mismatch tolerance. Another immediate and desirable consequence is that, it is now easy to use string edit distance instead of Hamming distance as in [21,16] to define pattern occurrences. We note that annotating substrings on input sequences directly to represent patterns rather than specifying the forms of the patterns had appeared in the context of annotated sequence comparison to support patterns of various types (see [9,Sections 3…”

Multiple sequence alignment for phylogenetic purposes

“…The alignment between a consistent subset of the anchor sites then proceeds using a normal progressive global strategy. Programs that adopt this general approach include MACAW (Schuler et al 1991), the various developments of DiAlign (Morgenstern 1999;Subramanian et al 2005;Morgenstern et al 2006), DbClustal (Thompson et al 2000), FMAlign (Chakrabarti et al 2004), MuSiC (Tsai et al 2004;Lu and Huang 2005), RAlign (Sammeth and Heringa 2006), and Sigma (Siddharthan 2006). Align-m (Van Walle et al 2004) can also be seen as fitting into this category.…”