Survival Analysis on Rare Events Using Group-Regularized Multi-Response Cox Regression

Published in Bioinformatics, 2021

In this paper led by Ruilin Li, we describe a new method to fit a sparse Cox Model for multiple time-to-event phenotypes from a large-scale (> 1 million features) genetic dataset.

This is a product of collaboration with the Hastie and the Tibshirani labs and built on other techniques that we have developed in the Rivas lab.

Citation: R. Li, Y. Tanigawa, J. M. Justesen, J. Taylor, T. Hastie, R. Tibshirani, M. A. Rivas, Survival Analysis on Rare Events Using Group-Regularized Multi-Response Cox Regression. Bioinformatics (2021). https://doi.org/10.1093/bioinformatics/btab095