LAMSA | Datasets2Tools

General Information

Description	Fast split read alignment with long approximate matches
Homepage	https://github.com/hitbc/LAMSA

Publications

Bioinformatics (2016)

LAMSA: fast split read alignment with long approximate matches

Bo Liu; Yan Gao; Yadong Wang

Motivation : Read length is continuously increasing with the development of novel high-throughput sequencing technologies, which has enormous potentials on cutting-edge genomic studies. However, longer reads could more frequently span the breakpoints of structural variants (SVs) than that of shorter reads. This may greatly influence read alignment, since most state-of-the-art aligners are designed for handling relatively small variants in a co-linear alignment framework. Meanwhile, long read alignment is still not as efficient as that of short reads, which could be also a bottleneck for the upcoming wide application.

Results: We propose long approximate matches-based split aligner (LAMSA), a novel split read alignment approach. It takes the advantage of the rareness of SVs to implement a specifically designed two-step strategy. That is, LAMSA initially splits the read into relatively long fragments and co-linearly align them to solve the small variations or sequencing errors, and mitigate the effect of repeats. The alignments of the fragments are then used for implementing a sparse dynamic programming-based split alignment approach to handle the large or non-co-linear variants. We benchmarked LAMSA with simulated and real datasets having various read lengths and sequencing error rates, the results demonstrate that it is substantially faster than the state-of-the-art long read aligners; meanwhile, it also has good ability to handle various categories of SVs.

Availability and Implementation: LAMSA is available at https://github.com/hitbc/LAMSA

Contact: Ydwang@hit.edu.cn

Supplementary information: Supplementary data are available at Bioinformatics online.

DOI: https://doi.org/10.1093/bioinformatics/btw594

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