Kmer-SSR: a fast and exhaustive SSR search algorithm

Motivation: One of the main challenges with bioinformatics software is that the size and complexity of datasets necessitate trading speed for accuracy, or completeness. To combat this problem of computational complexity, a plethora of heuristic algorithms have arisen that report a ‘good enough’ solution to biological questions. However, in instances such as Simple Sequence Repeats (SSRs), a ‘good enough’ solution may not accurately portray results in population genetics, phylogenetics and forensics, which require accurate SSRs to calculate intra‐ and inter‐species interactions. Results: We present Kmer‐SSR, which finds all SSRs faster than most heuristic SSR identification algorithms in a parallelized, easy‐to‐use manner. The exhaustive Kmer‐SSR option has 100% precision and 100% recall and accurately identifies every SSR of any specified length. To identify more biologically pertinent SSRs, we also developed several filters that allow users to easily view a subset of SSRs based on user input. Kmer‐SSR, coupled with the filter options, accurately and intuitively identifies SSRs quickly and in a more user‐friendly manner than any other SSR identification algorithm. Availability and implementation: The source code is freely available on GitHub at https://github.com/ridgelab/Kmer‐SSR. Contact: perry.ridge@byu.edu