Quantification of Real Time Polymerase Chain Reaction (PCR) Data

• Activity Number: 301
• Type: Contributed
• Date/Time: Tuesday, August 2, 2011 : 8:30 AM to 10:20 AM
• Sponsor: Biometrics Section
• Author(s): Xuelin Huang*+ and Wei Wei and Ning Jing
• Companies: The University of Texas MD Anderson Cancer Center and The University of Texas MD Anderson Cancer Center and The University of Texas Health Science Center at Houston
• Keywords: Bioinformatics ; DNA ; Microarray ; Polymerase chain reaction ; PCR ; Quantification

Abstract

The quantitative real-time polymerase chain reaction (PCR) can now amplify even a tiny amount of DNA material to a detectable level and then back-calculate its initial number of molecules from the real-time PCR curve. It has been the golden standard used in modern molecular biology research to confirm discoveries by other techniques, such as microarrays and single nucleotide polymorphism (SNP) arrays. However, so far, most of the methods for the aforementioned back-calculation from PCR curves were developed by biologists. There is a great room for improvement by statisticians. Various parametric S-shape models have been proposed for such data. Although they all visually fit well to the PCR data curve, their performances on estimating the initial amount of DNA molecules are not satisfactory. We propose a new approach for the quantification of PCR data to improve the data quality.