A Bayesian approach for genotyping single nucleotide polymorphisms (SNPs). (2018)

• Record Type: Journal Article
• Authors: Sheikhi, Ali; Ramsey, David
• Is Part Of: International journal of data mining and bioinformatics. Volume 20:Number 4(2018)
• Page Start: 341
• Page End: 361
• Publication Date: 2018
• Subjects: Bayesian -- genotype -- SNP -- single nucleotide polymorphism; Data mining -- Periodicals; Bioinformatics -- Periodicals; 006.312
• Languages: English
• ISSNs: 1748-5673

Abstract

Genotyping is the process of determining the genetic make-up (genotype) of an individual by examining the individual's DNA sequence. It reveals the alleles an individual has inherited from their parents. Single Nucleotide Polymorphism (SNP) genotyping first involves identifying SNPs that are a common source of genetic variation. Genotyping of SNPs has become extremely important to researchers working to understand and treat disease. Most SNPs are biallelic, thus the genotype is defined by the three possible combinations of the two alleles. In this study, we present a Bayesian approach for genotyping the detected SNPs. We also present the results of genotyping the real genome sequence data.