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Microarrays Data Analysis with R/S+ and GGobi
This two-day beginner to intermediate course is designed for people involved in microarrays data analysis.
Newly developed analysis methods for microarrays data analysis are often available from open-source (R,Bioconductor, etc) and can also be used in S+. Thanks to the great flexibility of R and S languages these methods and tools can be easily adapted to own data. In this course, we'll review R/S packages (librairies) for microarray analysis. We'll also explore GGobi interactive and dynamic graphics for microarrays analysis, statistical learning methods and strategies for large data.
Course Topics
Day 1
R/S System: Overview
Microarray Data; Standards, Data Structures
Data Pre-processing and Normalization
R/S Packages for Microarray Analysis
Bioconductor
Day 2
GGobi
Handling Missing Values
Statistical Learning Methods
Classification
Cluster Analysis
Inference, Strategies for Large Data
Course Format
This course consists of a series of short lectures with demonstrations and interactive sessions for the participants. Each student is provided with bound copies of the notes and a CD-ROM containing all example and exercises used on the course.
Duration and Prerequisites
Duration: 2 days
Before attending this course, you should have some basic computer experience:
use a keyboard
running software under windows and/or unix environment
