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 highthroughput 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
This calls for new approaches needed to deal with this issue of high memory requirements in suffix trees REF .
slaMEM: efficient retrieval of maximal exact matches using a sampled LCP array
Bioinformatics
Bioinformatics
Computer Science Medicine