Jul 18, 2018  
Graduate Catalog 2014 - 2015 
    
Graduate Catalog 2014 - 2015 [ARCHIVED CATALOG]

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MTH 571 - Statistical Methods for Genetic Data

(4 credits)
Prerequisite: MTH 514 or permission of the instructor. This is an introduction to quantitative methods assoicated with the analysis of human genetic data, with an emphasis on applied projects aimed at prediction of disease status of a new sample on the basis of observed samples and identification of biomarkers leading to human disease. Topics will include overview of microarray, proteomics, and metablomics data, overview of supervised learning, linear methods for classification, kernel methods, boosting and additive trees, neural networks, support vector machines and flexible discriminants, and unsupervised learning. Students must be familiar with matrix notation and the statistical programming language R will be used in this course.


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