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
|Number of pages||3|
|State||Published - Sep 1 2016|
Bibliographical noteFunding 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.
© 2016 The Author 2016. Published by Oxford University Press.
ASJC Scopus subject areas
- Statistics and Probability
- Molecular Biology
- Computer Science Applications
- Computational Theory and Mathematics
- Computational Mathematics