Instructor: Dr. Claudia Rangel, Head of the Computational Genomics Group at the National Institute of Genomic Medicine, Mexico City, and Adjunct Professor of Mathematics CGU (firstname.lastname@example.org)
Course Time and Location: Saturday, 10:00AM to 12:50PM; the course will meet online (real time) through Elluminate. Students may take the course from any convenient location where internet access is available.
Prerequisites: competency in scientific computing, linear algebra, an upper division course in statistics, familiarity with basic biology, access to a computer on which the Elluminate software can be run (requires latest JAVA runtime environment).
Statistical Analysis of microarray data
- The biological problem
- Modern Microarray technology - How does it work?
- The high-dimensional small sample size data problem
- Key elements in a good experiment design
- Identifying sources of variation
- Statistical methods and algorithms for error detection and correction
- Statistical analysis workflow
- Software tools: R and bioconductor
- Computational implementation of workflow methods and algorithms in R
Microarray Data Interpretation
- Use of linear models for analysis and assessment of differential expression
- Gene selection (Empirical Bayes, volcano plots)
- Gene classification (Clustering, heatmaps)
Registered Students: Contact Professor Rangel by e-mail at email@example.com to receive further information on how to attend the first class meeting and set up your computer for Elluminate.