High-throughput next generation sequencing of cDNA, i.e. RNA-Seq, presents an unprecedented resource for characterizing the alternative splicing (AS) in complex eukaryotic transcriptomes. Accumulating evidences indicate that AS is developmentally regulated, but the precise responses of AS event to development is not well understood. Here, we describe a new method, based on an adjusted beta-distribution model, for detection of differential AS patterns from RNA-Seq data comparisons. Applying our method to two datasets of RNA-Seq for zika infection in human cells and pollen tissue in Arabidopsis thaliana, we identified 1,871 differentially AS events for 1,394 protein-coding genes in human and 496 differentially AS events for 358 protein-coding genes in Arabidopsis, respectively. The results included known AS events reported before as well as novel events, which demonstrate that the biological replicates are important in the effective identification using ß-distribution. With a high accurate rate, our new method in differential AS identification will facilitate future investigation on transcriptomic annotation.