SA-SSR: A suffix array-based algorithm for exhaustive and efficient SSR discovery in large genetic sequences

B. D. Pickett; S. M. Karlinsey; C. E. Penrod; M. J. Cormier; M. T.W. Ebbert; D. K. Shiozawa; C. J. Whipple; P. G. Ridge

doi:10.1093/bioinformatics/btw298

SA-SSR: A suffix array-based algorithm for exhaustive and efficient SSR discovery in large genetic sequences

B. D. Pickett, S. M. Karlinsey, C. E. Penrod, M. J. Cormier, M. T.W. Ebbert, D. K. Shiozawa, C. J. Whipple, P. G. Ridge

Research output: Contribution to journal › Article › peer-review

12 Scopus citations

Abstract

Simple Sequence Repeats (SSRs) are used to address a variety of research questions in a variety of fields (e.g. population genetics, phylogenetics, forensics, etc.), due to their high mutability within and between species. Here, we present an innovative algorithm, SA-SSR, based on suffix and longest common prefix arrays for efficiently detecting SSRs in large sets of sequences. Existing SSR detection applications are hampered by one or more limitations (i.e. speed, accuracy, ease-of-use, etc.). Our algorithm addresses these challenges while being the most comprehensive and correct SSR detection software available. SA-SSR is 100% accurate and detected >1000 more SSRs than the second best algorithm, while offering greater control to the user than any existing software. Availability and implementation: SA-SSR is freely available at http://github.com/ridgelab/SA-SSR

Original language	English
Pages (from-to)	2707-2709
Number of pages	3
Journal	Bioinformatics
Volume	32
Issue number	17
DOIs	https://doi.org/10.1093/bioinformatics/btw298
State	Published - Sep 1 2016

Bibliographical note

Funding Information:
This work was supported by start-up funds from Brigham Young University to PGR and a mentoring environment grant from Brigham Young University to CJW.

Publisher Copyright:
© 2016 The Author 2016. Published by Oxford University Press.

ASJC Scopus subject areas

Statistics and Probability
Biochemistry
Molecular Biology
Computer Science Applications
Computational Theory and Mathematics
Computational Mathematics

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abstract = "Simple Sequence Repeats (SSRs) are used to address a variety of research questions in a variety of fields (e.g. population genetics, phylogenetics, forensics, etc.), due to their high mutability within and between species. Here, we present an innovative algorithm, SA-SSR, based on suffix and longest common prefix arrays for efficiently detecting SSRs in large sets of sequences. Existing SSR detection applications are hampered by one or more limitations (i.e. speed, accuracy, ease-of-use, etc.). Our algorithm addresses these challenges while being the most comprehensive and correct SSR detection software available. SA-SSR is 100% accurate and detected >1000 more SSRs than the second best algorithm, while offering greater control to the user than any existing software. Availability and implementation: SA-SSR is freely available at http://github.com/ridgelab/SA-SSR",

author = "Pickett, {B. D.} and Karlinsey, {S. M.} and Penrod, {C. E.} and Cormier, {M. J.} and Ebbert, {M. T.W.} and Shiozawa, {D. K.} and Whipple, {C. J.} and Ridge, {P. G.}",

note = "Funding Information: This work was supported by start-up funds from Brigham Young University to PGR and a mentoring environment grant from Brigham Young University to CJW. Publisher Copyright: {\textcopyright} 2016 The Author 2016. Published by Oxford University Press.",

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AU - Penrod, C. E.

AU - Cormier, M. J.

AU - Ebbert, M. T.W.

AU - Shiozawa, D. K.

AU - Whipple, C. J.

AU - Ridge, P. G.

N1 - Funding Information: This work was supported by start-up funds from Brigham Young University to PGR and a mentoring environment grant from Brigham Young University to CJW. Publisher Copyright: © 2016 The Author 2016. Published by Oxford University Press.

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N2 - Simple Sequence Repeats (SSRs) are used to address a variety of research questions in a variety of fields (e.g. population genetics, phylogenetics, forensics, etc.), due to their high mutability within and between species. Here, we present an innovative algorithm, SA-SSR, based on suffix and longest common prefix arrays for efficiently detecting SSRs in large sets of sequences. Existing SSR detection applications are hampered by one or more limitations (i.e. speed, accuracy, ease-of-use, etc.). Our algorithm addresses these challenges while being the most comprehensive and correct SSR detection software available. SA-SSR is 100% accurate and detected >1000 more SSRs than the second best algorithm, while offering greater control to the user than any existing software. Availability and implementation: SA-SSR is freely available at http://github.com/ridgelab/SA-SSR

AB - Simple Sequence Repeats (SSRs) are used to address a variety of research questions in a variety of fields (e.g. population genetics, phylogenetics, forensics, etc.), due to their high mutability within and between species. Here, we present an innovative algorithm, SA-SSR, based on suffix and longest common prefix arrays for efficiently detecting SSRs in large sets of sequences. Existing SSR detection applications are hampered by one or more limitations (i.e. speed, accuracy, ease-of-use, etc.). Our algorithm addresses these challenges while being the most comprehensive and correct SSR detection software available. SA-SSR is 100% accurate and detected >1000 more SSRs than the second best algorithm, while offering greater control to the user than any existing software. Availability and implementation: SA-SSR is freely available at http://github.com/ridgelab/SA-SSR

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SA-SSR: A suffix array-based algorithm for exhaustive and efficient SSR discovery in large genetic sequences

Abstract

Bibliographical note

ASJC Scopus subject areas

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