The lunch will be served 12:00, while the talk starts at 12:15.

Speaker: Emilie Eliseussen Ødegaard (Doctoral Research Fellow at the Institute of Basic Medical Sciences, UiO)

Location: UiO (8th floor of Niels Henrik Abels hus) and Zoom.

Title: Rank-based Bayesian variable selection for genome-wide transcriptomic analyses

Abstract: Variable selection is crucial in high-dimensional omics-based analyses, since it is biologically reasonable to assume only a subset of non-noisy features contributes to the data structures. However, the task is particularly hard in an unsupervised setting, and a priori ad hoc variable selection is still a very frequent approach, despite the evident drawbacks and lack of reproducibility. We propose a Bayesian variable selection approach for rank-based unsupervised transcriptomic analysis. Making use of data rankings instead of the actual continuous measurements increases the robustness of conclusions when compared to classical statistical methods, and embedding variable selection into the inferential tasks allows complete reproducibility. Specifically, we develop a novel extension of the Bayesian Mallows model for variable selection that allows for a full probabilistic analysis, leading to coherent quantification of uncertainties. Simulation studies demonstrate the versatility and robustness of the proposed method in a variety of scenarios, as well as its superiority with respect to several competitors when varying the data dimension or data generating process. We use the novel approach to analyse genome-wide RNAseq gene expression data from ovarian cancer patients: several genes that affect cancer development are correctly detected in a completely unsupervised fashion, showing the usefulness of the method in the context of signature discovery for cancer genomics. Moreover, the possibility to also perform uncertainty quantification plays a key role in the subsequent biological investigation.

This talk will be based on the following paper published in Statistics in Medicine, which is joint work with Thomas Fleischer and Valeria Vitelli:

Eliseussen, E, Fleischer, T, Vitelli, V. Rank-based Bayesian variable selection for genome-wide transcriptomic analyses. Statistics in Medicine. 2022; 41( 23): 4532– 4553. doi:10.1002/sim.9524

Join Zoom Meeting:
https://uio.zoom.us/j/63199595088?pwd=Y05GYkJwR1dCUHFhUnlGMFpsdGc3UT09

Meeting ID: 631 9959 5088
Passcode: 302551

Welcome!
Best regards,
Thea Roksvåg and Lars Henry Berge Olsen.

Emilie Eliseussen Ødegaard