Spring 2009 Thursday, January 15   Speaker: Bret Hanlon Department of Statistical Science Cornell University Title: Inference for Quantitation Parameters in Polymerase Chain Reactions via Branching Processes with Random Effects Abstract: Quantitative polymerase chain reaction (qPCR) is one of the most widely used tools for gene quantification. Most of the existing methods for analyzing qPCR data fail to account for the sources of variability present in the PCR dynamics. In this talk, I develop a branching process model with random effects to account for this variability, and describe a new inferential procedure for the quantitation parameters. I illustrate the effectiveness of my methods using both simulated and experimental data. (This talk is based on a joint work with Professor Anand Vidyashankar, Cornell University).

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