Statistical Analysis of Genetic and Gene Expression Data MolPAGE
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Objective

Microarrays are costly, both in time and resources. Statistical expertise in the design and analysis of microarray experiments is therefore in growing demand. In an initial part of the Course, international experts will lecture on data quality assessment, experimental design, data pre-processing and normalization, model-based data analysis, differential expression testing, and on statistical issues in multiple testing. In the second part, emphasis will be given to statistical problems involved in the integration of DNA sequence and gene expression data, with the aim of uncovering important functional dependencies. The third part will cover methods for representing complex multivariate distributions in the form of networks, or graphs, with an underlying probabilistic interpretation in terms of conditional independence. Emphasis will be given to applications of these methods in the investigation of complex genetic systems and of causal associations between gene expression and disease. The fifth – and last – day will cover advanced applications of the methods. The Course is addressed to a non necessarily statistical audience.