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read-mapping

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BLEND is a mechanism that can efficiently find fuzzy seed matches between sequences to significantly improve the performance and accuracy while reducing the memory space usage of two important applications: 1) finding overlapping reads and 2) read mapping. Described by Firtina et al. (published in NARGAB https://doi.org/10.1093/nargab/lqad004)

  • Updated May 10, 2023
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Lightweight single-html-file-based Genome Segments playground for Visualize genome features cluster(gene arrow map or other features), add synteny among genome fragments or add crosslink among features, add short(PE/MP)/long reads(pacbio or nanopore) mapping or snpindel in vcf(not support complex sv yet), support all CIGAR of sam alignment, dire…

  • Updated Jul 12, 2020
  • HTML

Source code for the software implementations of the GenASM algorithms proposed in our MICRO 2020 paper: Senol Cali et. al., "GenASM: A High-Performance, Low-Power Approximate String Matching Acceleration Framework for Genome Sequence Analysis" at https://people.inf.ethz.ch/omutlu/pub/GenASM-approximate-string-matching-framework-for-genome-analys…

  • Updated Dec 19, 2022
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GenStore is the first in-storage processing system designed for genome sequence analysis that greatly reduces both data movement and computational overheads of genome sequence analysis by exploiting low-cost and accurate in-storage filters. Described in the ASPLOS 2022 paper by Mansouri Ghiasi et al. at https://people.inf.ethz.ch/omutlu/pub/GenS…

  • Updated Apr 6, 2022
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Genome-on-Diet is a fast and memory-frugal framework for exemplifying sparsified genomics for read mapping, containment search, and metagenomic profiling. It is much faster & more memory-efficient than minimap2 for Illumina, HiFi, and ONT reads. Described by Alser et al. (preliminary version: https://arxiv.org/abs/2211.08157).

  • Updated Sep 4, 2024
  • Roff

GateSeeder is the first near-memory CPU-FPGA co-design for alleviating both the compute-bound and memory-bound bottlenecks in short and long-read mapping. GateSeeder outperforms Minimap2 by up to 40.3×, 4.8×, and 2.3× when mapping real ONT, HiFi, and Illumina reads, respectively.

  • Updated Oct 3, 2023
  • C

The first work to provide a comprehensive survey of a prominent set of algorithmic improvement and hardware acceleration efforts for the entire genome analysis pipeline used for the three most prominent sequencing data, short reads (Illumina), ultra-long reads (ONT), and accurate long reads (HiFi). Described in arXiv (2022) by Alser et al. https…

  • Updated Jun 14, 2022

A systematic survey of algorithmic foundations and methodologies across 107 alignment methods (1988-2021), for both short and long reads. We provide a rigorous experimental evaluation of 11 read aligners to demonstrate the effect of these underlying algorithms on speed and efficiency of read alignment. Described by Alser et al. at https://arxiv.…

  • Updated Jul 7, 2021
  • Jupyter Notebook

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