Abstract
A versatile algorithm is developed to model PCR on a computer. The method is based on a modification of the coalescent process and provides a general framework to analyse data from PCR. It allows for incorporation of the dynamics of the replication process as described in terms of the number of starting template molecules and cycle-dependent PCR efficiency. The simulation method generates, as a first step, the genealogy of a set of sequences sampled from a final PCR product. In a second step a mutation process is superimposed and the resulting data set is analysed. The efficiency of our algorithm enables us to get reliable approximations of various sample distributions. We demonstrate the relevance of our method with two applications: maximum likelihood estimation of the error rate in PCR and a test of homogeneity of the template.