MATH 425E. Statistical Genomics

3.00
This course will cover key statistical concepts and methods necessary for extracting biological insights from high throughput genomic experiments. The topics include: discrete probability distributions (binomial, Poisson, negative binomial, and multinomial), joint probability distributions, conditional probabilities, prior and posterior probabilities, and Bayesian inference. Students will learn how to access high throughput genomic data from public websites, relevant preprocessing and analyses methods. This course will also study gene network, groups and patterns using cluster and principal component analysis.