PUNAS: A Parallel Ungapped-Alignment-Featured Seed Verification Algorithm for Next-Generation Sequencing Read Alignment

Chan, Yuandong; Xu, Kai; Lan, Haidong; Wei-guo, Liu; Liu, Yongchao; Schmidt, Bertil

doi:10.1109/ipdps.2017.35

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Cited by 4 publications

(2 citation statements)

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“…In this paper, we propose a novel energy-efficient read mapper using a single FPGA system-on-chip (SoC) platform. Read mapping includes two stages, filtering and verification [9], [14], [21]- [23]. The first stage identifies candidate locations in the reference genome for the reads and the second stage calculates the exact alignment of the reads to the reference genome.…”

Section: Introductionmentioning

confidence: 99%

An FPGA Based Energy-Efficient Read Mapper With Parallel Filtering and In-Situ Verification

Gudur

Maheshwari

Acharyya

et al. 2022

IEEE/ACM Trans. Comput. Biol. and Bioinf.

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Section: Introductionmentioning

confidence: 99%

An FPGA Based Energy-Efficient Read Mapper With Parallel Filtering and In-Situ Verification

Gudur

Maheshwari

Acharyya

et al. 2022

IEEE/ACM Trans. Comput. Biol. and Bioinf.

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“…With the development of next-generation sequencing (NGS) technology, the size of datasets has expanded dramatically, resulting in memory-intensive. With the application of high-performance computing devices, macro-genomic research parallelization schemes are widely used for sequence indexing [1,2], sequence alignment [3,4] and genome assembly [5,6]. However, the simple parallelization of traditional algorithms poses significant performance problems.…”

mentioning

confidence: 99%

High‐frequency k‐mer counting at low memory footprint

Mocheng

Liu

Xiao

et al. 2022

Electronics Letters

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Genomics data analysis requires efficient tools to address the vast amount of data generated by current next‐generation sequencing technologies. K‐mer counting works face difficulties in balancing high memory overhead with statistical precision. We designed a high‐frequency k‐mer statistical computation based on the Space Saving algorithm and a novel hash table structure, which reduces the memory overhead by 46% while ensuring high computational efficiency.

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