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.
Reference:
Das Roy, P, Basu, C, Das, S and Das Gupta, A. 2014. Statistical studies for SNP association in acute coronary syndrome ex vivo use of agonists and nanoparticles. Calcutta Statistical Association Bulletin, pp 221-230
Das Roy, P., Basu, C., Das, S., & Das Gupta, A. (2014). Statistical studies for SNP association in acute coronary syndrome ex vivo use of agonists and nanoparticles. http://hdl.handle.net/10204/7584
Das Roy, P, C Basu, Sonali Das, and A Das Gupta "Statistical studies for SNP association in acute coronary syndrome ex vivo use of agonists and nanoparticles." (2014) http://hdl.handle.net/10204/7584
Das Roy P, Basu C, Das S, Das Gupta A. Statistical studies for SNP association in acute coronary syndrome ex vivo use of agonists and nanoparticles. 2014; http://hdl.handle.net/10204/7584.
Copyright: 2014 Calcutta Statistical Association Bulletin. This is the pre/post print version. The definitive version is Published in Calcutta Statistical Association Bulletin, pp 221-230
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