LAMSA: fast split read alignment with long approximate matches.
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.



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.



LAMSA is available at https://github.com/hitbc/LAMSA CONTACT: Ydwang@hit.edu.cnSupplementary information: Supplementary data are available at Bioinformatics online.
Center for Bioinformatics, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China.
Bo
B
Liu
Center for Bioinformatics, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China.
Yan
Y
Gao
Center for Bioinformatics, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China.
Yadong
Y
Wang
D000465:Algorithms; D015894:Genome, Human; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D006801:Humans; D017422:Sequence Analysis, DNA / Q000379:methods*; D012984:Software