ASPECT: Alternative SPlicing Events Classification with Transformer

The data and models for ASPECT: Alternative Splicing Event Classification with Transformers. We present ASPECT, an alternative splicing event classification framework built upon DNABERT-2 with Byte Pair Encoding (BPE) tokenization. Across multiple binary alternative splicing event pair classification tasks, ASPECT achieves consistently strong performance as measured by AUC, F1-score, and accuracy, demonstrating reliable discrimination between closely related splicing event types. Importantly, ASPECT demonstrates consistent performance when applied to TCGA BRCA cancer-associated splicing events reconstructed from SpliceSeq annotations, supporting its applicability beyond the canonical splicing events used for training. Availability: The open-source code, data, and detailed documentation used in this study are available at https://github.com/OluwadareLab/ASPECT.