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Large-scale sequence comparisons with sourmash

N. Tessa Pierce, Luiz Irber, Taylor Reiter, Phillip Brooks, C. Titus Brown
doi: https://doi.org/10.1101/687285
N. Tessa Pierce
1Department of Population Health and Reproduction, School of Veterinary Medicine, University of California, Davis
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Luiz Irber
1Department of Population Health and Reproduction, School of Veterinary Medicine, University of California, Davis
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Taylor Reiter
1Department of Population Health and Reproduction, School of Veterinary Medicine, University of California, Davis
2Food Science Graduate Group, University of California, Davis
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Phillip Brooks
1Department of Population Health and Reproduction, School of Veterinary Medicine, University of California, Davis
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C. Titus Brown
1Department of Population Health and Reproduction, School of Veterinary Medicine, University of California, Davis
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  • For correspondence: ctbrown@ucdavis.edu
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Abstract

The sourmash software package uses MinHash-based sketching to create “signatures”, compressed representations of DNA, RNA, and protein sequences, that can be stored, searched, explored, and taxonomically annotated. sourmash signatures can be used to estimate sequence similarity between very large data sets quickly and in low memory, and can be used to search large databases of genomes for matches to query genomes and metagenomes. sourmash is implemented in C++, Rust, and Python, and is freely available under the BSD license at http://github.com/dib-lab/sourmash.

Footnotes

  • https://osf.io/kesh2/

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted June 30, 2019.
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Large-scale sequence comparisons with sourmash
N. Tessa Pierce, Luiz Irber, Taylor Reiter, Phillip Brooks, C. Titus Brown
bioRxiv 687285; doi: https://doi.org/10.1101/687285
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Large-scale sequence comparisons with sourmash
N. Tessa Pierce, Luiz Irber, Taylor Reiter, Phillip Brooks, C. Titus Brown
bioRxiv 687285; doi: https://doi.org/10.1101/687285

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