Kmer-SSR: a fast and exhaustive SSR search algorithm.
Bioinformatics
; 33(24): 3922-3928, 2017 Dec 15.
Article
en En
| MEDLINE
| ID: mdl-28968741
ABSTRACT
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.
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Algoritmos
/
Programas Informáticos
/
Repeticiones de Microsatélite
Tipo de estudio:
Prognostic_studies
Idioma:
En
Revista:
Bioinformatics
Asunto de la revista:
INFORMATICA MEDICA
Año:
2017
Tipo del documento:
Article
País de afiliación:
Estados Unidos