Alternative splicing is a main source of generating a highly dynamic human proteome. It enables exons of genes to recombine in different ways when a segment of DNA is transcribed into messenger RNAs (mRNAs). There are seven patterns of alternative splicing which are known as typical ways in human genes. Alternative splicing has been found to be associated with many human diseases. This work proposes a novel method to identify alternative splicing patterns and analyze the distribution variations in a given gene expression process from mRNA read sequence data generated by next-generation sequencing (NGS) technology. The proposed method is based on parallel mapping of mRNA read sequence data to both genomic and transcriptomic reference sequences, and analyzes the mRNA read sequence data coverage and junctions spanning two exons. The preliminary results conducted with simulated data showed the prominent efficiency in identifying and quantifying events of alternative splicing.