Methods and apparatus for identifying alternative splicing events. The method comprises receiving a dataset of percent spliced in (PS I) values for each of a plurality of biological samples, wherein the plurality of biological samples includes a first population of samples having a first characteristic and a second population of samples having a second characteristic different from the first characteristic, fitting, to the dataset, a probabilistic model to identify clusters of samples in the dataset, calculating cluster characteristics for each of the clusters, filtering the clusters based, at least in part, on the cluster characteristics to identify a subset of clusters, each of which is associated with an alternative splicing event, and storing on the at least one storage device, information associated with the identified alternative splicing events.