Abstract:
|
Gene expression studies have yielded a number of fundamental insights that have changed the course of cancer diagnosis, prognosis, and treatment. Although useful, most previous studies rely on measurements averaged over thousands of cells which can miss and in some cases misrepresent signal, and are not amenable for precise quantification and characterization of tumor heterogeneity. This is particularly challenging for biomarker development where assays that are sensitive and specific across a heterogeneous patient population are required. Single-cell RNA-seq (scRNA-seq) is a promising technology that allows for genome-wide expression profiling within a single cell, and thereby has the potential to address some of the limitations inherent to bulk RNA-seq experiments. In this talk, I will provide an overview of the opportunities and challenges provided by scRNA-seq data and the implications for biomarker development, and will also discuss a statistical method we have developed for characterizing gene expression dynamics and sample heterogeneity using scRNA-seq data from cancer patient samples.
|
ASA Meetings Department
732 North Washington Street, Alexandria, VA 22314
(703) 684-1221 • meetings@amstat.org
Copyright © American Statistical Association.