We are covering statistical techniques commonly used in the analysis of high throughput data. This includes inference in the context of high-throughput data, distance and clustering for high-dimensional data, dimension reduction, machine learning, modeling including empirical Bayes and hierarchical models and advanced exploratory data analysis.

This research is been supported in part by NIH grant R25GM114818.