Computational Tool Choice Impacts CRISPR Spacer-Proto spacer Detection

MOTIVATION: CRISPR spacer-protospacer matching is widely used to infer host-virus interactions in microbial and viromics studies, but the choice of sequence search or alignment tool and its reporting behavior is often under-evaluated for this specific task. RESULTS: Using synthetic, semi-synthetic, and real datasets, we benchmarked commonly used tools and observed substantial differences in recall, runtime, and resource usage across distance metrics and thresholds. Our analyses support practical defaults for large-scale spacer-target matching and clarify trade-offs between exhaustive and heuristic approaches. AVAILABILITY: Source code and benchmark workflows are available at https://github.com/UriNeri/spacer_matching_bench. Data and run artifacts are archived on Zenodo (https://doi.org/10.5281/zenodo.15171878). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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Publication Details

Journal
Bioinformatics
Published
2026-06-29
DOI
https://doi.org/10.1093/bioinformatics/btag394
Primary Topic
CRISPR and Genetic Engineering
Type
article
Field-Weighted Citation Impact
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article

Computational Tool Choice Impacts CRISPR Spacer-Proto spacer Detection

Rick Beeloo, Simon Roux, Uri Neri, Antônio Pedro Camargo et al.
Bioinformatics
CRISPR and Genetic Engineering
article

Computational Tool Choice Impacts CRISPR Spacer-Proto spacer Detection

Rick Beeloo, Simon Roux, Uri Neri, Antônio Pedro Camargo, Brian Bushnell
article en

Abstract

MOTIVATION: CRISPR spacer-protospacer matching is widely used to infer host-virus interactions in microbial and viromics studies, but the choice of sequence search or alignment tool and its reporting behavior is often under-evaluated for this specific task. RESULTS: Using synthetic, semi-synthetic, and real datasets, we benchmarked commonly used tools and observed substantial differences in recall, runtime, and resource usage across distance metrics and thresholds. Our analyses support practical defaults for large-scale spacer-target matching and clarify trade-offs between exhaustive and heuristic approaches. AVAILABILITY: Source code and benchmark workflows are available at https://github.com/UriNeri/spacer_matching_bench. Data and run artifacts are archived on Zenodo (https://doi.org/10.5281/zenodo.15171878). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Bioinformatics
University of Applied Sciences Utrecht (NL), Utrecht University (NL), Joint Genome Institute (US)
Openalex Percentile: Top 11%
CRISPR and Genetic Engineering
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