RT Journal Article SR Electronic T1 LEAP: A Generalization of the Landau-Vishkin Algorithm with Custom Gap Penalties JF bioRxiv FD Cold Spring Harbor Laboratory SP 133157 DO 10.1101/133157 A1 Hongyi Xin A1 Jeremie Kim A1 Sunny Nahar A1 Can Alkan A1 Onur Mutlu YR 2017 UL http://biorxiv.org/content/early/2017/05/07/133157.abstract AB Motivation Approximate String Matching is a pivotal problem in the field of computer science. It serves as an integral component for many string algorithms, most notably, DNA read mapping and alignment. The improved LV algorithm proposes an improved dynamic programming strategy over the banded Smith-Waterman algorithm but suffers from support of a limited selection of scoring schemes. In this paper, we propose the Leaping Toad problem, a generalization of the approximate string matching problem, as well as LEAP, a generalization of the Landau-Vishkin’s algorithm that solves the Leaping Toad problem under a broader selection of scoring schemes.Results We benchmarked LEAP against 3 state-of-the-art approximate string matching implementations. We show that when using a bit-vectorized de Bruijn sequence based optimization, LEAP is up to 7.4x faster than the state-of-the-art bit-vector Levenshtein distance implementation and up to 32x faster than the state-of-the-art affine-gap-penalty parallel Needleman Wunsch Implementation.Availability We provide an implementation of LEAP in C++ at github.com/CMU-SAFARI/LEAP.Contact hxin{at}cmu.edu, calkan{at}cs.bilkent.edu.tr or onur.mutlu{at}inf.ethz.ch