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

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

PROVIDER: PRJNA793881 | ENA |

REPOSITORIES: ENA

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	SRR17414711_1.fastq.gz	Fastqsanger.gz

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

Project description: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. In total, we generated and analyzed ~1.1 billion nanopore RNA-seq reads covering 30 human tissue samples and three human cell lines. ESPRESSO and its companion dataset provide a useful resource for studying the RNA repertoire of eukaryotic transcriptomes.

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Made in error

Project description:Made in error

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