LAMSA: fast split read alignment with long approximate matches.MOTIVATION
 We propose long approximate matches-based split aligner (LAMSA), a novel split read alignment approach.  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.  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.
LAMSA
LAMSA: fast split read alignment with long approximate matches.MOTIVATION
 We propose long approximate matches-based split aligner (LAMSA), a novel split read alignment approach.  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.  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.
LAMSA
LAMSA: fast split read alignment with long approximate matches.MOTIVATION
 We propose long approximate matches-based split aligner (LAMSA), a novel split read alignment approach.  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.  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.
LAMSA