Ben Raphael, PhD, professor in the Department of Computer Science at Princeton University will deliver the talk titled "Quantifying Tumor Heterogeneity using Bulk, Single-cell, and Spatial Sequencing".

Join the Zoom. 

Meeting ID: 967 9363 3223

Passcode: 328834

Abstract:

Tumors are heterogeneous mixtures of normal and cancerous cells with distinct genetic and transcriptional profiles.  In this talk, I will present several computational approaches to quantify tumor heterogeneity and reconstruct tumor evolution using data from bulk, single-cell, and spatial sequencing technologies.  For bulk and targeted single-cell DNA sequencing, I will describe methods that reconstruct tumor evolution using both somatic single-nucleotide mutations and copy number aberrations, properly accounting for overlap and interactions between these two common classes of mutations.  For low-coverage whole-genome single-cell sequencing, I will describe an algorithm CHISEL to compute allele-specific copy numbers and an application of this algorithm to reconstruct tumor evolution for thousands of single cells from a breast tumor.  For spatial transcriptomics, I will describe a new algorithm PASTE to align and integrate spatial transcriptomics data from multiple adjacent tissue sections using both transcriptional and spatial similarity.   I will illustrate the advantages of multi-section alignment and integration for quantifying heterogeneity in squamous cell carcinomas and inferring cell types in human tissues.