Pairwise alignment of nucleotide sequences using maximal exact matches
نویسندگان
چکیده
منابع مشابه
Multiple Genome Alignment by Clustering Pairwise Matches
We have developed a multiple genome alignment algorithm by using a sequence clustering algorithm to combine local pairwise genome sequence matches produced by pairwise genome alignments, e.g, BLASTZ. Sequence clustering algorithms often generate clusters of sequences such that there exists a common shared region among all sequences in each cluster. To use a sequence clustering algorithm for gen...
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We have developed essaMEM, a tool for finding maximal exact matches that can be used in genome comparison and read mapping. essaMEM enhances an existing sparse suffix array implementation with a sparse child array. Tests indicate that the enhanced algorithm for finding maximal exact matches is much faster, while maintaining the same memory footprint. In this way, sparse suffix arrays remain com...
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Bioinformatics, through the sequencing of the full genomes for many species, is increasingly relying on efficient global alignment tools exhibiting both high sensitivity and specificity. Many computational algorithms have been applied for solving the sequence alignment problem. Dynamic programming, statistical methods, approximation and heuristic algorithms are the most common methods appli...
متن کاملSpace Efficient Computation of Rare Maximal Exact Matches between Multiple Sequences
In this article, we propose a new method for computing rare maximal exact matches between multiple sequences. A rare match between k sequences S(1), ... , S(k) is a string that occurs at most t(i)-times in the sequence S(i), where the t(i) > 0 are user-defined thresholds. First, the suffix tree of one of the sequences (the reference sequence) is built, and then the other sequences are matched s...
متن کاملslaMEM: efficient retrieval of maximal exact matches using a sampled LCP array
MOTIVATION Maximal exact matches, or just MEMs, are a powerful tool in the context of multiple sequence alignment and approximate string matching. The most efficient algorithms to collect them are based on compressed indexes that rely on longest common prefix array-centered data structures. However, their space-efficient representations make use of encoding techniques that are expensive from a ...
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ژورنال
عنوان ژورنال: BMC Bioinformatics
سال: 2019
ISSN: 1471-2105
DOI: 10.1186/s12859-019-2827-0