Assessing the reproducibility of high-throughput experiments with a Bayesian hierarchical model

What you will learn

A Bayesian hierarchical model framework and a set of computational toolkits to evaluate the overall reproducibility of high-throughput biological experiments, and identify irreproducible and reproducible signals via rigorous false discovery rate control procedures.

Authors

Yi Zhao

Matthew Sampson

Xiaoquan (William) Wen

Assessments of Reproducibility, Theory and Definition