Long-read sequencing enables the direct measurement of RNA molecules. However, this data must be processed to reconstruct transcript sequences, their abundances, and their configuration as alternative splicing isoforms in genes. In this project, we aim at developing novel computational algorithms that will make possible the study of transcriptome variation from long-read sequencing data. We plan to apply these tools to uncover new molecular features in cancer and inherited disorders.