High-Dimensional Omics Data Analysis

This subject provides a detailed introduction to the statistical analysis of high-dimensional transcriptomic data, i.e. data consisting of expression measurements of thousands of genes from each sampled individual. Transcriptomic analysis is essential for identifying differences in the activity level of genes, providing novel insights into biological mechanisms, e.g. cell signalling, development, or disease. Researchers globally rely on transcriptomic analysis to study conditions like cancer and neurodegenerative disorders. Topics in this subject include: data visualisation; normalisation; differential expression; and gene-set testing. This subject also shows how the principles of transcriptomic analysis generalise to the analysis of other kinds of high-dimensional “omics” data, e.g. epigenomic and proteomic data.