Addressing Within-Subject Genomic Heterogeneity

• Activity Number: 145
• Type: Contributed
• Date/Time: Monday, August 5, 2013 : 8:30 AM to 10:20 AM
• Sponsor: Biometrics Section
• Author(s): Matthew Nicholson McCall*+ and Anthony Almudevar
• Companies: University of Rochester Medical Center and University of Rochester Medical Center
• Keywords: genomics ; cancer ; heterogeneity ; extrema ; biomarker

Abstract

Tissue biopsy followed by histopathology, or more recently genomic analysis, is a standard procedure to assess the type, severity, and prognosis of many diseases, particularly cancer. Within-subject genomic heterogeneity, in which a single patient displays vastly different genomic profiles between samples, represents a challenge to such analysis. Here we show that in the presence of within-subject heterogeneity, an extremum statistic may outperform a measure of centeral tendency in capturing the genomic signature of interest. We use a simple heterogeneity model to explore situations in which the mean is outperformed by an extremum and demonstrate the applicability of this approach on a hepatocellular carcinoma data set.