JSM 2005 Online Program

JSM Activity #CE_01C

This is the preliminary program for the 2005 Joint Statistical Meetings in Minneapolis, Minnesota. Currently included in this program is the "technical" program, schedule of invited, topic contributed, regular contributed and poster sessions; Continuing Education courses (August 7-10, 2005); and Committee and Business Meetings. This on-line program will be updated frequently to reflect the most current revisions.

To View the Program:
You may choose to view all activities of the program or just parts of it at any one time. All activities are arranged by date and time.

The views expressed here are those of the individual authors
and not necessarily those of the ASA or its board, officers, or staff.

The Program has labeled the meeting rooms with "letters" preceding the name of the room, designating in which facility the room is located:

Minneapolis Convention Center = “MCC” Hilton Minneapolis Hotel = “H” Hyatt Regency Minneapolis = “HY”

Back to main JSM 2005 Program page

Legend:

= Applied Session,

= Theme Session,

= Presenter


		Add To My Program
CE_01C	Sun, 8/7/05, 8:00 AM - 4:00 PM	MCC-L100 I
Analysis of Gene Expression Data - Continuation of 2 Day Course - Continuing Education - Course
ASA
Instructor(s): Terence P. Speed, University of California, Berkeley, Benjamin M. Bolstad, University of California, Berkeley, Yee Hwa Jean Yang, University of California, San Francisco, James Wettenhall, Walter and Eliza Hall Institute of Medical Research
This short course will be an introduction to the statistical analysis of gene expression data from cDNA, long-oligonucleotide and high-density short oligonucleotide microarrays, and serial analysis of gene expression (SAGE) data. We will begin with a short biological introduction, and then turn to brief descriptions of representative microarray platforms and the SAGE process. Preprocessing and QC issues will be addressed, as will issues related to probe or tag identity and data visualization. Following this introductory material, attention will turn to the gene expression measurements themselves, and the identification of differentially expressed (d.e.) genes using replicated data. With this background, it is possible to discuss design issues underlying the search for d.e. genes, including the different types of replicates, and the dependencies inherent in microarray gene expression data. The next topic to be discussed is the annotation of d.e. genes using the Gene Ontology, and the search for d.e. sets of genes. The remainder of the short course will be devoted to more specialized topics including classification, clustering, and the analysis of time course data. Participants are expected to bring their own laptops and to have downloaded the specified software and datasets prior to arriving in Minneapolis, or to purchase CDs with the same on site. The course will be a series of 8 30-45 minute lectures followed by 45-60 minute lab sessions, with lengthy breaks that we hope will keep the pace leisurely. Experience with statistical methods in data analysis is essential, but no previous knowledge of gene expression data is required. The course will include the opportunity to apply statistical methods to several data sets that will be provided.