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pmid:40286290

RabbitSketch: a high-performance sketching library for genome analysis.

Tong Zhang · Zekun Yin · Xiaoming Xu · Lifeng Yan · Fangjin Zhu · Xiaohui Duan · Bertil Schmidt · Weiguo Liu

Bioinformatics (Oxford, England) · 2025 doi:10.1093/bioinformatics/btaf249

Paper

complete

Experiment

partial

Data

partial

Analysis

absent

Execution

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title
RabbitSketch: a high-performance sketching library for genome analysis.
doi
10.1093/bioinformatics/btaf249
pmid
40286290
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Tong Zhang
[1]
Zekun Yin
[2]
Xiaoming Xu
[3]
Lifeng Yan
[4]
Fangjin Zhu
[5]
Xiaohui Duan
[6]
Bertil Schmidt
[7]
Weiguo Liu
journal
Bioinformatics (Oxford, England)
year
2025
abstract
SUMMARY: We present RabbitSketch, a highly optimized library of sketching algorithms such as MinHash, OrderMinHash, and HyperLogLog that can exploit the power of modern multi-core CPUs. It provides significant speedups compared to existing implementations, ranging from 2.30× to 49.55×, as well as flexible and easy-to-use interfaces for both Python and C++. As a result, the similarity analysis of 455GB genomic data can be completed in only 5 minutes using RabbitSketch with merely 20 lines of Python code. As a case study, we enhanced RabbitTClust by integrating RabbitSketch's Kssd algorithm, resulting in a 1.54× speedup with no loss in accuracy. AVAILABILITY AND IMPLEMENTATION: RabbitSketch is available at https://github.com/RabbitBio/RabbitSketch with an archived version at Zenodo: https://doi.org/10.5281/zenodo.14903962. Detailed API documentation is available at https://rabbitsketch.readthedocs.io/en/latest.
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