Molecular Profiling and Biomarker Discovery
Transcriptomic studies are routinely used in genomic studies to detect changes in mRNA expression levels and have been key in developing biomarkers for several diseases. These experiments have fundamental statistical and data processing challenges associated with them. This course covers the statistical aspects of experimental design, biological and technical replicates, preprocessing, quality assessment, parametric and non-parametric statistical tests, multiple-hypothesis testing, P-value correction and false discovery rates, visualization techniques (e.g. heatmaps, volcano plots), and biological significance (e.g. functional annotation, pathways, hypergeometric tests, gene set enrichment).