Microarray Statistics Modules

 

 

Biochemistry Modules:

 

Module 1: Spot gridding and fold-change selection

 

Module 2: Normalization of microarray data

 

Module 3: Clustering, comparison, prediction, and GO term analysis

 

For questions about the biology modules and/or examples of student responses to the questions asked within the modules, please contact:

 

Laura Hoopes

Halstead-Bent Professor of Biology

Pomona College

lhoopes@pomona.edu

Statistics Modules:

 

Module 1: Spot gridding and segmentation

 

Module 2: Downloading data from Stanford Microarray Database

 

Module 3: Normalizing microarray data (R help, example activity)

 

Module 4: SAM (siggenes) for class comparisons (R help)

 

Module 5: Hierarchical clustering

 

Module 6: Prediction Analysis for Microarrays (PAM) classification 

 

 

For questions about the statistics modules and/or examples of student responses to the questions asked within the modules, please contact:

 

Jo Hardin

Assistant Professor of Mathematics

Pomona College

jo.hardin@pomona.edu

 

These modules were originally created as part of a Howard Hughes Medical Institute grant to Pomona College.  They have been used in a Biochemistry class (Biology department) as well as a course on Statistical Analysis of Genetic Data (Mathematics Department.)

 

We have designed the modules so that they can all be used in a single class or used individually for a course or half-course.  Additionally, we have modified the modules slightly for use in either a biology or statistics course.

 

The modules are described in some detail in:

J. Hardin, L. Hoopes, R. Murphy; Analyzing DNA Microarrays with Undergraduate Statisticians, Proceedings of the Seventh International Conference on Teaching Statistics, 2006.

 

This work would not have been possible without generous funding by grants from the Howard Hughes Medical Institute and the NSF Major Research Instrumentation program.