报告题目：Bayesian Nonparametric Clustering with Feature Selection for Spatially Resolved Transcriptomics Data

报 告 人：胡冠宇教授（美国休斯顿德克萨斯州大学）

报告时间：2025年5月19日  15:30-16:30

报告地点：格物楼528报告厅

报告摘要：

Current computational approaches often rely on heuristic data preprocessing and arbitrary cluster number prespecification, leading to considerable information loss and consequently, suboptimal downstream analysis. In response to these challenges, we introduce BNPSpace, a novel Bayesian nonparametric spatial clustering framework that directly models SRT count data. BNPSpace facilitates the partitioning of the whole spatial domain, which is characterized by substantial heterogeneity, into homogeneous spatial domains with similar molecular characteristics while identifying a parsimonious set of discriminating genes among different spatial domains. Moreover, BNPSpace incorporates spatial information through a Markov random field prior model, encouraging a smooth and biologically meaningful partition pattern. We assess the performance of BNPSpace utilizing both simulated and real SRT data.

报告人简介：

胡冠宇，休斯敦德克萨斯州大学健康科学中心教授，他的研究主要集中在贝叶斯非参数方法、空间和时空统计学、点过程和因果推断。此外，还从事临床试验、空间转录组学、区域经济学、环境科学、教育测量和体育数据的分析，他是Biometrics，Annals of Applied Statistics，Environmental and Ecological Statistics，Statistics and its interface的副主编，担任ASA体育统计部分的主席和SBA东亚分会的项缍錧扁刑目主席，当选为ISI委员。