ESPRESSO: Robust discovery and quantification of transcript isoforms from error-prone long-read RNA-seq data.

ABSTRACT: Long-read RNA sequencing (RNA-seq) holds great potential for characterizing transcriptome variation and full-length transcript isoforms, but the relatively high error rate of current long-read sequencing platforms poses a major challenge. We present ESPRESSO, a computational tool for robust discovery and quantification of transcript isoforms from error-prone long reads. ESPRESSO jointly considers alignments of all long reads aligned to a gene and uses error profiles of individual reads to improve the identification of splice junctions and the discovery of their corresponding transcript isoforms. On both a synthetic spike-in RNA sample and human RNA samples, ESPRESSO outperforms multiple contemporary tools in not only transcript isoform discovery but also transcript isoform quantification.

SUBMITTER: Gao Y 

PROVIDER: S-EPMC9858503 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature