GateKeeper: a new hardware architecture for accelerating pre-alignment in DNA short read mapping
Open access
Date
2017-11-01Type
- Journal Article
ETH Bibliography
yes
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Abstract
Motivation
High throughput DNA sequencing (HTS) technologies generate an excessive number of small DNA segments -called short reads- that cause significant computational burden. To analyze the entire genome, each of the billions of short reads must be mapped to a reference genome based on the similarity between a read and ‘candidate’ locations in that reference genome. The similarity measurement, called alignment, formulated as an approximate string matching problem, is the computational bottleneck because: (i) it is implemented using quadratic-time dynamic programming algorithms and (ii) the majority of candidate locations in the reference genome do not align with a given read due to high dissimilarity. Calculating the alignment of such incorrect candidate locations consumes an overwhelming majority of a modern read mapper’s execution time. Therefore, it is crucial to develop a fast and effective filter that can detect incorrect candidate locations and eliminate them before invoking computationally costly alignment algorithms.
Results
We propose GateKeeper, a new hardware accelerator that functions as a pre-alignment step that quickly filters out most incorrect candidate locations. GateKeeper is the first design to accelerate pre-alignment using Field-Programmable Gate Arrays (FPGAs), which can perform pre-alignment much faster than software. When implemented on a single FPGA chip, GateKeeper maintains high accuracy (on average >96%) while providing, on average, 90-fold and 130-fold speedup over the state-of-the-art software pre-alignment techniques, Adjacency Filter and Shifted Hamming Distance (SHD), respectively. The addition of GateKeeper as a pre-alignment step can reduce the verification time of the mrFAST mapper by a factor of 10. Show more
Permanent link
https://doi.org/10.3929/ethz-b-000220096Publication status
publishedExternal links
Journal / series
BioinformaticsVolume
Pages / Article No.
Publisher
Oxford University PressOrganisational unit
09483 - Mutlu, Onur / Mutlu, Onur
Notes
It was possible to publish this article open access thanks to a Swiss National Licence with the publisher.More
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ETH Bibliography
yes
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