Special Topics Course on

Microarray Data Analysis

University of California, Santa Cruz Extension

Description

Microarray technology enables the monitoring of the expression levels of thousands of genes in a single experiment. This revolutionary breakthrough is expected to transform the diagnosis and treatment of diseases, and holds great promise for functional genomics. In order to take advantage of this technology's full potential, however, the flood of data being produced will need to be analyzed by statistical methods and computer algorithms in various ways, to make useful predictions, or to make new discoveries. This short course presents the statistical and algorithmic foundations of microarray data analysis.

Text and Topics

The material will be covered from a short electronic book written by the author on the subject. This book will be made available free to all who enroll in the course. Here are the chapters from this book. We will try to cover them all.

• Introduction: What microarray data is, what we can learn from it, what statistics has to offer.
• Preprocessing microarray data.
• Measuring (dis)similarity of expression patterns.
• Visualizing microarray data.
• Cluster analysis of microarray data.
• Identifying genes expressed differently in two populations.
• Identifying genes expressed differently in paired samples.
• Classifying samples from two populations.

Software

The course will also disseminate (and exchange) information about current public domain or commercial microarray data analysis software. Information will be disseminated at the course's private web site.

Prerequisites

Data Analysis, Modeling, and Visualization for Bioinformatics or equivalent.

Assignments

There will be no mandatory assignments. Optional practice assignments (not to be turned in) will be posted to the course's private web site.