Biomedical Data Science Seminar Series, BRB Gaulton Auditorium

Title: Tumor subclone detection and niche differential expression analysis on spatial transcriptomics data

This week hosted by CCDS – invited by Qi Long, PhD

Abstract: 

Single cells influence, and are shaped by, their local tissue microenvironment.  High resolution technologies for in situ profiling of gene expression at the transcriptome scale are rapidly maturing, enabling the detailed interrogation of the distribution of cell types in situ as well as the elucidation of local signaling patterns between cell types.  In this talk, I will describe new computational methods for the analysis of spatial transcriptomics data, and illustrate their application to the study of cancer.  First, I will focus on the detection of somatic copy number aberrations from spatial transcriptomic and single cell data, and the use of somatic copy numbers in the differentiation of malignant from normal tissue and the characterization of tumor subclonal evolution.  Next, I will discuss niche-differential expression (niche-DE) analysis.  Niche-DE identifies cell-type specific niche-associated genes, defined as genes whose single cell expression is significantly up- or down-regulated in the context of specific spatial niches.  Although niche-DE is conceptually defined on the single-cell level, we show that niche-DE genes can be recovered from lower resolution spatial transcriptomic (ST) data where each observation is a spot containing a mixture of cell types.  We apply the methods to the study of the tumor microenvironment on spatial transcriptomic data from multiple cancer types.

Bio:

Dr. Zhang is a Ge Li and Ning Zhao Professor of Statistics in The Wharton School at University of Pennsylvania.  Her research focuses primarily on the development of statistical methods and computational algorithms for the analysis of genomic data.  She has made contributions to copy number and structural variant detection and to intra-tumor genetic heterogeneity modelling, and recently she has made myriad methodological contributions to the analysis of single-cell sequencing data.  In Statistics, she has made contributions to change-point analysis, variable selection, and model selection.

Dr. Zhang obtained her Ph.D. in Statistics in 2005 from Stanford University.  After one year of postdoctoral training at University of California, Berkeley, she returned to the Department of Statistics at Stanford University as Assistant Professor in 2006.  She received the Sloan Fellowship in 2011, and formally moved to University of Pennsylvania in 2012.  She was awarded the Medallion Lectureship by the Institute of Mathematical Statistics in 2021.  Her work has been funded by grants from the NSF and NIH.  At Penn, she is a member of the Graduate Group in Genomics and Computational Biology, and currently serves as the Vice Dean of the Wharton Doctoral Program.