Statistical studies for SNP association in acute coronary syndrome ex vivo use of agonists and nanoparticles

Abstract

In this paper we apply statistical classification techniques to a case-control study. The data analysed relates to Acute Coronary Syndrome (ACS). We discuss an adaptation of the Naijve Bayes method, and assess the results using an analysis of deviance based approach. Analysis of deviance is used to rank the driver variables, such as phenotype and genotype variables to their relative contribution to classify a new case into one of ACS or non-ACS group. Results from the case study reveal that a combination of Single Nucleotide Polymorphism 2 and Single Nucleotide Polymorphism 4 is the most important, and the aggregation of platelets on addition of Adenosine-di-phosphate along with nano particles the next most important factors in classifying an unseen patient into one of the two groups. Some limitations and future analyses are also discussed.