ArticleBioinformatics (Oxford, England)2017
GateKeeper: a new hardware architecture for accelerating pre-alignment in DNA short read mapping.
Article in Bioinformatics (Oxford, England), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Taming large-scale genomic analyses via sparsified genomics.Nature communications · 2025Article
- PPML-Omics: A privacy-preserving federated machine learning method protects patients' privacy in omic data.Science advances · 2024Article
- WFA-GPU: gap-affine pairwise read-alignment using GPUs.Bioinformatics (Oxford, England) · 2023Article
- A framework for high-throughput sequence alignment using real processing-in-memory systems.Bioinformatics (Oxford, England) · 2023Article
- From molecules to genomic variations: Accelerating genome analysis via intelligent algorithms and architectures.Computational and structural biotechnology journal · 2022Review
- Technology dictates algorithms: recent developments in read alignment.Genome biology · 2021Review
- Hardware acceleration of genomics data analysis: challenges and opportunities.Bioinformatics (Oxford, England) · 2021Article
- Phylogenomic assessment of drug-resistant Mycobacterium tuberculosis strains from Beira, Mozambique.Tuberculosis (Edinburgh, Scotland) · 2020Article
- Shouji: a fast and efficient pre-alignment filter for sequence alignment.Bioinformatics (Oxford, England) · 2019Article
- Nanopore sequencing technology and tools for genome assembly: computational analysis of the current state, bottlenecks and future directions.Briefings in bioinformatics · 2019Review
- Pairwise alignment of nucleotide sequences using maximal exact matches.BMC bioinformatics · 2019Article
- GRIM-Filter: Fast seed location filtering in DNA read mapping using processing-in-memory technologies.BMC genomics · 2018Article
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Authors and funding
6 authors.
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Abstract
motivationHigh 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.
resultsWe 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. AVAILABILITY AND IMPLEMENTATION: https://github.com/BilkentCompGen/GateKeeper. CONTACT: mohammedalser@bilkent.edu.tr or onur.mutlu@inf.ethz.ch or calkan@cs.bilkent.edu.tr. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.