BMI219

Statistical Methods for Array and Sequence Data

This course is intended to expose students to approaches to formulating and tackling important data analytic problems that arise in the context of contemporary, high-throughput technologies. These include various array-based platforms and next generation sequencing technologies. Some application areas that will be addressed include ChIP-chip and ChIP-Seq studies, copy number variation, and epigenetics. It is expected that students will acquire the ability to frame statistical hypotheses in such settings and be able to identify corresponding data analytic techniques. While a selection of such techniques will be introduced here via case studies, they pertain to more broadly encountered research questions and study domains. Examples of methodologies described include data preprocessing approaches , multiple hypothesis testing, sequence analysis, clustering, and contemporary classification and regression methods.

Target audience: BMI, PQB, BMS students