School of Medicine
| Course Overview |
| More information |
| Flyer |
| Directions |
| CBMB |
The purpose of the one day short course is to introduce biomedical researchers to statistical issues in the design and analysis of microarray studies.
Target Audience: Scientists, researchers and data analysts who are planning and/or currently performing or analyzing microarray experiments.
Prerequisite: Familiarity with microarray technology and associated data structures.
Materials: Presentation notes have been posted for preview; black-and-white handouts will be distributed at the workshop.
Course Outline:
| 9:00 - 9:15 |
Sign-In |
| 9:15 - 9:30 |
Introduction Jean Yee Hwa Yang and Ru-Fang Yeh |
| 9:30 - 10:20 |
Lecture 1 Case Study 1: Two-sample analysis Ru-Fang Yeh Array experiments, featuring simple two group comparisons, are used to illustrate various methods ranging from pre-processing to higher level techniques. This lecture will also discuss methods for identification of differentially expressed genes, multiple testing concerns and identification of upstream regulatory sequences for groups of co-expressed genes. |
| 10:20 - 10:50 | Coffee Break |
| 10:50 - 11:40 |
Lecture 2 Case study 2: Designed / factorial microarray experiments Jean Yee Hwa Yang A factorial experiment is used to illustrate the application of linear models to identify genes with different time course profiles. Resources and tools for synthesizing results with gene ontology information will also be discussed. |
| 11:40 - 11:45 | Short Break |
| 11:45 - 12:15 |
Lecture 3 Case study 3: Discrimination / classification Jane Fridlyand Classification concepts are presented and illustrated with breast cancer gene expression data. The lecture will focus on two-sample classification problems but more complex scenarios will also be discussed. |
| 12:15 - 1:30 |
Lunch Break -- box lunch provided |
| 1:30 - 2:10 |
Lecture 4 Case study 4: Linked survival phenotypes Mark Segal Supervised approaches for handling linked phenotypes are described with emphasis on survival outcomes. Illustration makes recourse to microarray studies of diffuse large B-cell lymphoma. |
| 2:10 - 2:20 | Short Break |
| 2:20 - 3:00 |
Lecture 5 Analysis of oligonucleotide genome tiling arrays Simon Cawley |
| 3:00 - 3:30 |
Coffee Break |
| 3:30 - 4:00 |
Lecture 6 Introduction to array CGH Jane Fridlyand This lecture will introduce array comparative genomic hybridization and discuss some of the analytical techniques specific to array CGH technology. |
| 4:00 - 4:10 | Short Break |
| 4:10 - 5:00 |
Lecture 7 Recent technologies and applications Saunak Sen Overview of some recent research questions relating to SNP arrays, splice junction arrays and eQTL analysis. |
StatSci.org Microarray Data Analysis References Contact us with questions regarding course content. Registration is now closed. |
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