PATA: An algorithm for the analysis of microarray alternative splicing experiments

An algorithm for the analysis of data from microarray experiments applied to alternative splicing is proposed. The algorithm uses a probabilistic model to account for observed data and reduce noise in measurements. Unlike prior work, this model is based on the details of the molecular interactions that govern microarray experiments. This decreases the model's data requirements and makes it more accurate than its predecessors.;The algorithm is applied to two datasets from independent microarray experiments used in alternative splicing studies. For each dataset, its performance is compared with competing methods, including GenASAP [54]. In all cases, the algorithm outperforms its competitors.