Dissemin is shutting down on January 1st, 2025

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Oxford University Press, Bioinformatics, 19(37), p. 3349-3350, 2021

DOI: 10.1093/bioinformatics/btab196

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KEC: unique sequence search by K-mer exclusion

Journal article published in 2021 by Pavel Beran ORCID, Dagmar Stehlíková, Stephen P. Cohen ORCID, Vladislav Čurn
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Data provided by SHERPA/RoMEO

Abstract

Abstract Summary Searching for amino acid or nucleic acid sequences unique to one organism may be challenging depending on size of the available datasets. K-mer elimination by cross-reference (KEC) allows users to quickly and easily find unique sequences by providing target and non-target sequences. Due to its speed, it can be used for datasets of genomic size and can be run on desktop or laptop computers with modest specifications. Availability and implementation KEC is freely available for non-commercial purposes. Source code and executable binary files compiled for Linux, Mac and Windows can be downloaded from https://github.com/berybox/KEC. Supplementary information Supplementary data are available at Bioinformatics online.