AEnet

We construct a novel method named alternative splicing network(AEN) combining gene expression levels with AS patterns to analyze cellular heterogeneity, identify novel cell types, and infer the regulatory mechanisms of alternative splicing. By applying the AEN method to gastrula data, pan-cancer T-cell data, and lung cancer tumor cell data, we have successfully revealed the hidden alternative splicing heterogeneity in these cells and identified key alternative splicing events and related splicing factors during cell transformation. The application of AEN method provides new insights into the understanding of cellular heterogeneity and its related physiological and pathological processes.