General Information
| Description | Efficient retrieval of maximal exact matches using a sampled LCP array |
| Homepage | http://github.com/fjdf/slaMEM/ |
Publications
slaMEM: 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 computational point of view. With the deluge of data generated by high-throughput sequencing, new approaches need to be developed to deal with larger genomic sequences.
Results:
In this work, we have developed a new longest common prefix array-sampled representation, optimized to work with the backward search method inherently used by the FM-Index. Unlike previous implementations that sacrifice running time to have smaller space, ours lead to both a fast and a space-efficient approach. This implementation was used by the new software slaMEM, developed to efficiently retrieve MEMs. The results show that the new algorithm is competitive against existing state-of-the-art approaches.
Availability and implementation:
The software is implemented in C and is operating system independent. The source code is freely available for download at http://github.com/fjdf/slaMEM/ under the GPLv3 license.
Contact:
atf@inesc-id.pt
Supplementary information:
Supplementary data are available at Bioinformatics online.
Related Tools
Next-generation VariationHunter
Published June 2010
Combinatorial algorithms for transposon insertion discovery
kmacs
Published May 2014
The k -mismatch average common substring approach to alignment-free sequence comparison
sBWT
Published July 2016
Memory efficient implementation of the hardware-acceleration-friendly Schindler transform for the fast biological sequen...
FAIR Evaluation
Sorry, you must be signed in to evaluate this object.
