MDAGB08 Microarray Data Analysis using GEPAS and Babelomics

DNA microarrays constitute, no doubt, a paradigm among post-genomic technologies, which are characterised for producing large amounts of data, whose analysis and interpretation is not trivial. Microarray technologies allows querying living systems in a completely new way, but at the same time present new challenges in the way hypotheses must be tested and results have to be analysed.

Since the first papers published in the latest nineties the number of questions that have been addressed through this technique have both increased and diversified. Initial interest was focused on genes coexpressing across sets of experimental conditions, implying essentially the use of clustering techniques. More recently, however, the interest has switched to find genes differentially expressed among distinct classes of experiments, or correlated to diverse parameters. There is also much interest in robust methods for building predictors of clinical outcomes. Also, CGH-arrays (Albertson and Pinkel, 2003) are recently becoming an alternative for studying the relationship between chromosomal alterations affecting to copy number (which are behind many diseases) and gene expression. In addition, there is also a clear demand for methods that allow automatic transfer of biological information to the results of microarray experiments.

More details, applcation info: http://gtpb.igc.gulbenkian.pt/bicourses/

This course covers the state-of-the-art in the above mentioned topics, which are of major relevance in today's gene expression data analysis. Through sessions of theory and practical examples, the students will acquire the experience necessary to address scientific questions to gene expression array datasets and solve them. Special attention will be devoted to important (despite frequently ignored) aspects in microarray data analysis, such as multiple testing or functional annotation. The course is designed to be a mixture of theoretical and practical sessions. The latter will require some familiarity with the use of web-based tools and knowledge of basics notions of statistics. Practical sessions will be carried out using the GEPAS (Herrero et al., 2003, 2004; Vaquerizas et al., 2005) environment, an integrated web tool for microarray data analysis, and the Babelomics suite (Al-Shahrour et al., 2005) for functional annotation of genome-scale experiments.