Simrank: Rapid and sensitive general-purpose k-mer search tool
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Updated: Jun 2, 2026

Introductory Analysis and Validation of CUT&RUN Sequencing Data
Published on: December 13, 2024
Todd Z DeSantis1, Keith Keller, Ulas Karaoz
1Ecology Department, Lawrence Berkeley National Laboratory, Berkeley, USA. tdesantis@lbl.gov
Background:
Terabyte-scale collections of string-encoded data are expected from consortia efforts such as the Human Microbiome Project http://nihroadmap.nih.gov/hmp. Intra- and inter-project data similarity searches are enabled by rapid k-mer matching strategies. Software applications for sequence database partitioning, guide tree estimation, molecular classification and alignment acceleration have benefited from embedded k-mer searches as sub-routines. However, a rapid, general-purpose, open-source, flexible, stand-alone k-mer tool has not been available.
Results:
Here we present a stand-alone utility, Simrank, which allows users to rapidly identify database strings the most similar to query strings. Performance testing of Simrank and related tools against DNA, RNA, protein and human-languages found Simrank 10X to 928X faster depending on the dataset.
Conclusions:
Simrank provides molecular ecologists with a high-throughput, open source choice for comparing large sequence sets to find similarity.
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