Performance improvement of SNP Search using multithread programming

Abstract

Pattern recognition is an important field in Bioinformatics and a well-known task is the search for Single Nucleotide Polymorphism (SNP). It is possible to search for a known SNP position and analyze it using patterns of DNA bases, called masks. Nonetheless, this process becomes computationally expensive as the amount of available genomic data increases. Thus, in this study, we have developed a parallelization scheme, based on multithread programming, to SNP analysis using masks. In our tests, we noticed that the proposed scheme improved the execution time in 98.05 times when compared with the sequential approach.