165-CellPhenoX: Explainable for Single-Cell Multi-Omics

Paper Talk · Oct 25, 2025 · 27m

The paper introduces CellPhenoX, a novel, explainable machine learning method designed to predict clinical phenotypes using single-cell multi-omics data. This computational tool integrates classification models, explainable AI (XAI) techniques, and a statistical framework to generate cell-specific Interpretable Scores that link cellular populations to clinical outcomes while accounting for covariates and interaction effects like sex and age. The authors demonstrate CellPhenoX's superior performance in identifying condition-associated cell populations, including rare ones, across simulated…