Single-Cell Trajectory Inference Framework Using Gaussian Mixture OT

Learn about scEGOT, a novel method for single-cell trajectory inference, in this 52-minute research talk that explores geometric data analysis in human biology. Discover how entropic Gaussian mixture optimal transport enables comprehensive trajectory analysis with seamless transitions between continuous and discrete problems while maintaining computational efficiency. Examine the practical application of scEGOT in studying human primordial germ cell-like cell (PGCLC) induction systems, where it successfully identified PGCLC progenitor populations and bifurcation timing. Follow the investigation that led to the discovery of NKX1-2, a previously unknown gene crucial for accurate PGCLC progenitor identification.