Lizarazo Simon, Maddox Kevin, Thanvi Abhi.

We propose and implement a hierarchical Bayesian model to assess gene set enrichment and diferential expression, extending concepts learned in the classroom to a practical, real-world application. We tested our model on simulated data and conducted a brief sensitivity analysis to justify the chosen priors. Finally, we applied the model to real sequencing data from patients with Glioblastoma Multiforme (GBM) and their respective controls, comparing our results to those obtained using conventional methods. Model validation on synthetic data and subsequent Bayesian analysis on real-world data provide preliminary indications of the viability of this method, with limitations and proposed future work discussed briefly.

If you want to learn more about this project, please feel free to check the pdf file attached.