报告题目：Conditional inference for high-dimensional multi-omics survival data

报 告 人：郝美玲 教授 对外经济贸易大学

报告时间：2026年1月13日 10：00-11：00

报告地点：腾讯会议579-571-742

校内联系人：王培洁 [email protected]

报告摘要：Multi-omics data present significant challenges for statistical inference due to the complex interdependencies among biological layers. In this paper, we introduce a novel Multi-Omics Factor-Adjusted Cox (MOFA-Cox) model for analyzing multi-omics survival data, effectively addressing the intricate correlations across various omics layers. We provide a factor-adjusted decorrelated score test for the MOFA-Cox model in high-dimensional survival analysis. Our method accommodates situations where the dimension of the parameters being tested exceeds the sample size, while not imposing a sparsity assumption on them. We establish the limiting null distribution of the proposed test and analyze its power under local alternatives. Numerical studies and an application to the TCGA breast cancer dataset demonstrate the effectiveness of our method.

报告人简介：郝美玲，对外经济贸易大学教授，香港理工大学博士，玛格丽特公主癌症研究中心博士后。主要研究领域：高维数据分析，生物统计，非参数统计，强化学习。主持国自然青年和面上基金项目，学术论文发表于Journal of the American Statistic Association, Journal of Machine Learning Research, Statistica Sinica, The Electronic Journal of Statistics, Computational Statistics & Data Analysis, Statistical Methods in Medical Research ， Statistics in Medecine等期刊。