Dynamic Programming for Single Nucleotide Polymorphism ID Identification in Systematic Association Studies

Abstract

Single nucleotide polymorphisms (SNPs) play an important role in personalized medicine. However, the SNP data reported in many association studies provide only the SNP nucleotide/amino acid position, without providing the SNP ID recorded in National Center for Biotechnology Information databases. A tool with the ability to provide SNP ID identification, with a user-friendly interface, is needed. In this paper, a dynamic programming algorithm was used to compare homologs when the processed input sequence is aligned with the SNP FASTA database. Our novel system provides a web-based tool that uses the National Center for Biotechnology Information dbSNP database, which provides SNP sequence identification and SNP FASTA formats. Freely selectable sequence formats for alignment can be used, including general sequence formats (ACGT, [dNTP1/dNTP2] or IUPAC formats) and orientation with bidirectional sequence matching. In contrast to the National Center for Biotechnology Information SNP-BLAST, the proposed system always provides the correct targeted SNP ID (SNP hit), as well as nearby SNPs (flanking hits), arranged in their chromosomal order and contig positions. The system also solves problems inherent in SNP-BLAST, which cannot always provide the correct SNP ID for a given input sequence. Therefore, this system constitutes a novel application which uses dynamic programming to identify SNP IDs from the literature and keyed-in sequences for systematic association studies. It is freely available at http://bio.kuas.edu.tw/SNPosition/.