GS010163  Analysis of Microarray Data

Baggerly, Keith. Three semester hours. Fall biannually. Prerequisite: Consent of instructor

This course is an introduction to the statistical and bioinformatic analysis of microarray data. The course covers both Affymetrix oligonucleotide arrays and two-color fluorescence cDNA microarrays. The course introduces students to the full range of processing microarray experiments, from experimental design, through image processing, background correction, normalization, and quality control, to the downstream statistical analysis of differential expression. The course includes coverage of the key statistical concept of multiple testing. The course covers common methods of pattern identification and pattern recognition in the context of microarrays. It also includes the bioinformatic interpretation of the results through tools to interact with public genome databases. All concepts will be illustrated through hands-on interaction with publicly available microarray data sets. Homework assignments will require some knowledge of R, a statistical programming language. The course will include a brief introduction to R. In addition to the biweekly assignments, student performance will be assessed through presentation of a final project.