Sequence searching allowing for non-overlapping adjacent unbalanced translocations

Unbalanced translocations are among the most frequent chromosomal alterations, accounted for 30% of all losses of heterozygosity, a major genetic event causing inactivation of tumor suppressor genes. Despite of their central role in genomic sequence analysis, little attention has been devoted to the problem of matching sequences allowing for this kind of chromosomal alteration. In this paper we investigate the approximate string matching problem when the edit operations are non-overlapping unbalanced translocations of adjacent factors. In particular, we first present a O(nm3)-time and O(m2)-space algorithm based on the dynamic-programming approach. Then we improve our first result by designing a second solution which makes use of the Directed Acyclic Word Graph of the pattern. In particular, we show that under the assumptions of equiprobability and independence of characters, our algorithm has a O(n log2σ m) average time complexity, for an alphabet of size σ, still maintaining the O(nm3)-time and the O(m2)-space complexity in the worst case. To the best of our knowledge this is the first solution in literature for the approximate string matching problem allowing for unbalanced translocations of factors

Efficient string-matching allowing for non-overlapping inversions

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Alignments with non-overlapping moves, inversions and tandem duplications in O ( n 4) time

Sequence alignment is a central problem in bioinformatics. The classical dynamic programming algorithm aligns two sequences by optimizing over possible insertions, deletions and substitutions. However, other evolutionary events can be observed, such as inversions, tandem duplications or moves (transpositions). It has been established that the extension of the problem to move operations is NP-complete. Previous work has shown that an extension restricted to non-overlapping inversions can be solved in O(n 3) with a restricted scoring scheme. In this paper, we show that the alignment problem extended to non-overlapping moves can be solved in O(n 5) for general scoring schemes, O(n 4log n) for concave scoring schemes and O(n 4) for restricted scoring schemes. Furthermore, we show that the alignment problem extended to non-overlapping moves, inversions and tandem duplications can be solved with the same time complexities. Finally, an example of an alignment with non-overlapping moves is provide

Canonical, Stable, General Mapping using Context Schemes

Motivation: Sequence mapping is the cornerstone of modern genomics. However, most existing sequence mapping algorithms are insufficiently general. Results: We introduce context schemes: a method that allows the unambiguous recognition of a reference base in a query sequence by testing the query for substrings from an algorithmically defined set. Context schemes only map when there is a unique best mapping, and define this criterion uniformly for all reference bases. Mappings under context schemes can also be made stable, so that extension of the query string (e.g. by increasing read length) will not alter the mapping of previously mapped positions. Context schemes are general in several senses. They natively support the detection of arbitrary complex, novel rearrangements relative to the reference. They can scale over orders of magnitude in query sequence length. Finally, they are trivially extensible to more complex reference structures, such as graphs, that incorporate additional variation. We demonstrate empirically the existence of high performance context schemes, and present efficient context scheme mapping algorithms. Availability and Implementation: The software test framework created for this work is available from https://registry.hub.docker.com/u/adamnovak/sequence-graphs/. Contact: [email protected] Supplementary Information: Six supplementary figures and one supplementary section are available with the online version of this article.Comment: Submission for Bioinformatic

String Synchronizing Sets: Sublinear-Time BWT Construction and Optimal LCE Data Structure

Burrows-Wheeler transform (BWT) is an invertible text transformation that, given a text $T$ of length $n$, permutes its symbols according to the lexicographic order of suffixes of $T$. BWT is one of the most heavily studied algorithms in data compression with numerous applications in indexing, sequence analysis, and bioinformatics. Its construction is a bottleneck in many scenarios, and settling the complexity of this task is one of the most important unsolved problems in sequence analysis that has remained open for 25 years. Given a binary string of length $n$, occupying $O(n/\log n)$ machine words, the BWT construction algorithm due to Hon et al. (SIAM J. Comput., 2009) runs in $O(n)$ time and $O(n/\log n)$ space. Recent advancements (Belazzougui, STOC 2014, and Munro et al., SODA 2017) focus on removing the alphabet-size dependency in the time complexity, but they still require $\Omega(n)$ time. In this paper, we propose the first algorithm that breaks the $O(n)$-time barrier for BWT construction. Given a binary string of length $n$, our procedure builds the Burrows-Wheeler transform in $O(n/\sqrt{\log n})$ time and $O(n/\log n)$ space. We complement this result with a conditional lower bound proving that any further progress in the time complexity of BWT construction would yield faster algorithms for the very well studied problem of counting inversions: it would improve the state-of-the-art $O(m\sqrt{\log m})$-time solution by Chan and P\v{a}tra\c{s}cu (SODA 2010). Our algorithm is based on a novel concept of string synchronizing sets, which is of independent interest. As one of the applications, we show that this technique lets us design a data structure of the optimal size $O(n/\log n)$ that answers Longest Common Extension queries (LCE queries) in $O(1)$ time and, furthermore, can be deterministically constructed in the optimal $O(n/\log n)$ time.Comment: Full version of a paper accepted to STOC 201

Comparative analysis of bacterial genomes: identification of divergent regions in mycobacterial strains using an anchor-based approach

Comparative genomic approaches are useful in identifying molecular differences between organisms. Currently available methods fail to identify small changes in genomes, such as expansion of short repetitive motifs and to analyse divergent sequences. In this report, we describe an anchor-based whole genome comparison (ABWGC) method. ABWGC is based on random sampling of anchor sequences from one genome, followed by analysis of sampled and homologous regions from the target genome. The method was applied to compare two strains of Mycobacterium tuberculosis CDC1551 and H37Rv. ABWGC was able to identify a total of 104 indels including 20 expansion of short repetitive sequences and five recombination events. It included 18 new unidentified genomic differences. ABWGC also identified 188 SNPs including eight new ones. The method was also used to compare M. tuberculosis H37Rv and M. avium genomes. ABWGC was able to correctly pick 1002 additional indels (size >100 nt) between the two organisms in contrast to MUMmer, a popular tool for comparative genomics. ABWGC was able to identify correctly repeat expansion and indels in a set of simulated sequences. The study also revealed important role of small repeat expansion in the evolution of M. tuberculosis strains