ML Estimation of DNA Initial Copy Number in Polymerase Chain Reaction (PCR) Processes

Abstract

Estimation of DNA copy number in a given biological sample is an extremely important problem in genomics. This problem is especially challenging when the number of the DNA strands is minuscule, which is often the case in applications such as pathogen and genetic mutation detection. A recently developed technique, real-time polymerase chain reaction (PCR), amplifies the number of initial target molecules by replicating them through a series of thermal cycles. Ideally, the number of target molecules doubles at the end of each cycle. However, in practice, due to biochemical noise the efficiency of the PCR reaction, defined as the fraction of target molecules which are successfully copied during a cycle, is always less than 1. In this paper, we formulate the problem of joint maximum-likelihood estimation of the PCR efficiency and the initial DNA copy number. As indicated by simulation studies, the performance of the proposed estimator is superior with respect to competing statistical approaches. Moreover, we compute the Cramer-Rao lower bound on the mean-square estimation error.