Inference for Quantitation Parameters in Polymerase Chain Reactions via Branching Processes With Random Effects

• 成果类型: Article
• 署名作者: Hanlon, Bret; Vidyashankar, Anand N.
• 署名单位: University of Wisconsin System; University of Wisconsin Madison
• 刊物名称: JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
• ISSN/ISSBN: 0162-1459
• DOI: 10.1198/jasa.2011.tm08601
• 发表日期: 2011
• 页码: 525-533
• 关键词: real-time pcr; quantification; rates

摘要

The quantitative polymerase chain reaction (qPCR) is a widely used tool for gene quantitation and has been applied extensively in several scientific areas. The current methods used for analyzing qPCR data fail to account for multiple sources of variability present in the PCR dynamics, leading to biased estimates and incorrect inference. In this article, we introduce a branching process model with random effects to account for within-reaction and between-reaction variability in PCR experiments. We describe, in terms of the observed fluorescence data, new statistical methodology for gene quantitation. Using simulations, PCR experiments, and asymptotic theory we demonstrate the improvements achieved by our methodology compared to existing methods. This article has supplemental materials online.