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PreprintCC BYbioRxiv

Homology-aware average nucleotide identity estimation at scale with TurboANI

  • J. Zhao
  • D. McDonald
  • L. Patel
  • C. Wang
  • A. Gonzalez
  • R. Knight1
  1. 1University of California San Diego
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Abstract

Here we introduce TurboANI, a fast homology-aware average nucleotide identity (ANI) estimation algorithm that implements the seed-chain-quasi-alignment scheme using SIMD seeding, compact indexing, lightweight chaining, and cache-friendly bitset sliding minwise hashing, achieving up to ~40,000-fold speedup over the alignment-based ANI algorithm with near-perfect agreement. TurboANI is also >40-fold faster than the state-of-the-art FastANI and ten-fold faster than skani while maintaining better accuracy. In the sensitive mode, it has a ten-fold higher true-ANI recovery rate than skani.

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Cite

BibTeXRIS
BibTeX
@misc{zhao2026homologyaware,
  title = {{Homology-aware average nucleotide identity estimation at scale with TurboANI}},
  author = {J. Zhao and D. McDonald and L. Patel and C. Wang and A. Gonzalez and R. Knight},
  howpublished = {bioRxiv},
  year = {2026},
  month = nov,
  doi = {10.64898/2026.11.05.764740},
  url = {https://www.biorxiv.org/content/10.64898/2026.11.05.764740v1},
  note = {CC BY},
}
RIS
TY  - UNPB
TI  - Homology-aware average nucleotide identity estimation at scale with TurboANI
AU  - J. Zhao
AU  - D. McDonald
AU  - L. Patel
AU  - C. Wang
AU  - A. Gonzalez
AU  - R. Knight
PY  - 2026
DA  - 2026/11/05
PB  - bioRxiv
DO  - 10.64898/2026.11.05.764740
UR  - https://www.biorxiv.org/content/10.64898/2026.11.05.764740v1
AB  - Here we introduce TurboANI, a fast homology-aware average nucleotide identity (ANI) estimation algorithm that implements the seed-chain-quasi-alignment scheme using SIMD seeding, compact indexing, lightweight chaining, and cache-friendly bitset sliding minwise hashing, achieving up to ~40,000-fold speedup over the alignment-based ANI algorithm with near-perfect agreement. TurboANI is also >40-fold faster than the state-of-the-art FastANI and ten-fold faster than skani while maintaining better accuracy. In the sensitive mode, it has a ten-fold higher true-ANI recovery rate than skani.
ER  -