Experiments on transcriptome analysis have resulted huge genes expression data related with specific temporal and spatial information. These data can be used in new genes identification，analysis of genes express patterns and the annotation of genomes, which may provide the reference standard for experiment design and result analysis of transcriptome experiments. Since the alternative splicing of eukaryotic genes have found to be universal and play an important role in physiology and pathology, systematic analysis of alternative splicing is becoming a new hotspot of functional genome research. Facing the immense and exponential increase of experimental express data and more new genomes getting sequenced, there is exigent of the strategy which can handle transcriptome sequences in large scale and automatic way. We elucidate the algorithms, the computing requirements and programs in different transcriptome sequences analysis systems and propose a strategy more suitable for large scale analysis of alternative splicing.