A short course on Computational and Statistical Aspects of Microarray Analysis

Kitasato University
July 14-25, 2003

Robert Gentleman

Schedule of Topics

Monday, July 14 Tuesday, July 15 Wednesday, July 16 Thursday, July 17 Friday, July 18
Lecture Introduction to Genome Biology R/S Programming Techniques DNA Microarray Data, Oligonucleotide Arrays Introduction to Bioconductor Experimental Design and Experimental Design Paper
Labs Lecture Con't Lab1, Lab2a Lab2b Lab3b Estrogen
Monday, July 21 Tuesday, July 22 Wednesday, July 23 Thursday, July 24 Friday, July 25
Lecture Holiday, No Lecture Microarray Experiments and Distances and Expression Measures Some Things Every Biologist Should Know About Machine Learning Classification in Microarray Experiments Clustering in Microarray Experiments
Labs Holiday Lab4 Lab5 Lab6, Lab7 Lab8

Lab materials

Lab1 Bioconductor Basics
Lab2a Bioinformatics (anotation package)
Lab2b An Introduction to Some Graphics in Bioconductor
Lab3a Introduction to Bioconductor's marray Packages
Lab3b Introduction to the affy package
Lab4 Differential Gene Expression
Lab5 Cluster Analysis Using R and Bioconductor
Lab6 Classification Using R and Bioconductor
Lab7 Analyzing Microarray Data: From Images to List of Candidate Genes
Lab8 Application of Machine Learning to Microarray Data, SVM and friends
Fred Hutchinson Cancer Research Center