Statistics Workshop Syllabus

| New Features in GeneSpring | Statistics and Algorithms | Data Analysis-Level I |
|Data Analysis-Level II | Data Analysis-Level III |
|Dates and Locations|

Course Description

Learn statistics from Silicon Genetics statistician, Peter Lambert. This one-day workshop is designed to provide fundamental concepts of statistics and their applications to microarray analysis. Discover how to identify differentially expressed genes using tools such as 1-way and 2-way ANOVA, multiple testing corrections, post-hoc test, Principal Component Analysis and the GeneSpring error model.

Relevant literature references will be included and ample time will be allocated for questions and discussions. GeneSpring will be used to illustrate examples. Prior knowledge of statistics is not required.

Required Prerequisites:
Users should feel comfortable with basic GeneSpring operations, especially data loading, normalization, specifying parameters and interpretations. Users should have attended the Level I workshop or attended the GeneSpring Data Loading online presentation.

Recommended Prerequisites:
Perform as much data analysis as possible using GeneSpring. Attend the Level II workshop and the "Basic Statistics for GeneSpring" online presentation.

Syllabus

8:15AM	Sign-in & Refreshments provided
8:30AM	Welcome & Introductions
Early morning	Statistics Primer/Review Basic probability theory Distributions Hypothesis testing
	Break
Mid morning	Determining Differential Expression T-tests ANOVA, 1-way and 2-way Parametric vs. Non-parametric Multiple testing and post-hoc tests
12:00PM	Lunch
	Break
Early afternoon	Principal Component Analysis Background Statistics and algorithms Application to expression data
	Break
Late afternoon	The GeneSpring Error Model Fitting the model and algorithms Error propagation
4:30PM	Class Ends