A short course on Computational and Statistical Aspects of Microarray Analysis

Kitasato University
July 14-25, 2003

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