Predictive genomics of cardioembolic stroke.
Cardioembolic stroke is a complex disease resulting from the interaction of numerous factors. Using data from Genes Affecting Stroke Risk and Outcome Study (GASROS), we show that a multivariate predictive model built using Bayesian networks is able to achieve a predictive accuracy of 86% on the fitted values as computed by the area under the receiver operating characteristic curve relative to that of the individual single nucleotide polymorphism with the highest prognostic performance (area under the receiver operating characteristic curve=60%).
Ramoni
Rachel Badovinac
RB
Harvard-Partners Center for Genetics and Genomics, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA. marco_ramoni@harvard.edu
Himes
Blanca E
BE
Sale
Michele M
MM
Furie
Karen L
KL
Ramoni
Marco F
MF
D001499:Bayes Theorem; D023281:Genomics; D006801:Humans; D008957:Models, Genetic; D015999:Multivariate Analysis; D020641:Polymorphism, Single Nucleotide / Q000235:genetics; D011379:Prognosis; D012307:Risk Factors; D020521:Stroke / Q000175:diagnosis / Q000453:epidemiology / Q000235:genetics*; D044465:White People / Q000235:genetics