A Graphical Model Formulation of the DNA Base-Calling Problem

A first order variable dependence (FOVD) probabilistic graphical model is introduced to capture the complex inter-event dependencies that are present in DNA sequencing data. In this framework, DNA base-calling is addressed as a parameter estimation problem using maximum likelihood methods. The FOVD model accounts for dependencies between neighboring alleles and statistically characterizes the size of signal peaks. Our experimental results suggest that the resulting unsupervised classification base-calling algorithms (i) achieve accuracy that exceeds on average that of the-state-of-the art base-callers, (ii) work well for a variety of data set types without requiring costly recalibration