Talk title: A unified approach for integrating spatial and single-cell transcriptomics data using deep generative models

报告人：杨灿 香港科技大学

报告时间： 2023年6月2日 上午9:00

#腾讯会议：435-686-9251

Abstract: The rapid emergence of spatial transcriptomics (ST) technologies is revolutionizing our understanding of tissue spatial architecture and their biology. Current ST technologies based on either next generation sequencing (seq-based approaches) or fluorescence in situ hybridization (image-based approaches), while providing hugely informative insights, remain unable to provide spatial characterization at transcriptome-wide single-cell resolution, limiting their usage in resolving detailed tissue structure and detecting cellular communications. To overcome these limitations, we developed SpatialScope, a unified approach to integrating scRNA-seq reference data and ST data that leverages deep generative models. With innovation in model and algorithm designs, SpatialScope not only enhances seq-based ST data to achieve single-cell resolution, but also accurately infers transcriptome-wide expression levels for image-based ST data. We demonstrate the utility of SpatialScope through comprehensive simulation studies and then apply it to real data from both seq-based and image-based ST approaches. SpatialScope provides a spatial characterization of tissue structures at transcriptome-wide single-cell resolution, greatly facilitating the downstream analysis of ST data, such as detection of cellular communication by identifying ligand-receptor interactions from seq-based ST data, localization of cellular subtypes, and detection of spatially differently expressed genes. The success of SpatialScope demonstrates the effectiveness of combining statistical principle with computing methods for real scientific data analytics. This is a joint work with PhD students Xiaomeng Wan, Jiashun Xiao, Sindy Sing Ting Tam, and collaborators Mingxuan Cai, Ryohichi Sugimura, Yang Wang, Xiang Wan, Zhixiang Lin, Angela Wu.

个人简介：杨灿博士现为香港科技大学罗台秦博士理学副教授，数学系副教授，大数据研究院教授成员。他分别于2003年和2006年在浙江大学获得工学学士学位和工学硕士学位，并于2011年在香港科技大学获得电子计算机工程博士学位。他是耶鲁大学的博士后（2011-2012）和副研究员（2012-2014）。他的研究领域专注于统计与计算方法的研发及其在大规模数据分析中的应用。他的研究论文发表在高影响力的期刊上，Nature Computational Science, Nature Communications, Annals of Statistics, Proceedings of the National Academy of Sciences, IEEE Transactions on Pattern Analysis and Machine Intelligence, 以及 The American Journal of Human Genetics。基于杨灿博士对数据科学的贡献，他获得了香港青年科学家一等奖(2012)，香港数学会杰出青年学者(2023)和香港科技大学理学院杰出科研奖(2023)。杨博士杨博士还得到香港政府创新技术基金的支持与产业界建立紧密合作。