Long-read RNA sequencing dataset of human pancreatic cancer cell lines.
Long-read RNA sequencing (RNA-seq) technologies have revolutionized transcriptomic research by enabling the sequencing of full-length RNA molecules, thus providing a more accurate characterization of
APA
Luo S, Feng J, et al. (2025). Long-read RNA sequencing dataset of human pancreatic cancer cell lines.. Scientific data, 12(1), 1653. https://doi.org/10.1038/s41597-025-05939-0
MLA
Luo S, et al.. "Long-read RNA sequencing dataset of human pancreatic cancer cell lines.." Scientific data, vol. 12, no. 1, 2025, pp. 1653.
PMID
41115920
Abstract
Long-read RNA sequencing (RNA-seq) technologies have revolutionized transcriptomic research by enabling the sequencing of full-length RNA molecules, thus providing a more accurate characterization of complex transcript isoforms than traditional short-read approaches. In this study, we present a high-coverage long-read transcriptome dataset generated using Oxford Nanopore Technologies' PromethION platform from ten human pancreatic cancer cell lines, with two biological replicates per line. The dataset comprises approximately 189.8 million reads across 20 samples, providing a valuable resource for studying transcript structures in pancreatic cancer. We perform systematic quality assessments, including read length, base quality, and gene body coverage, and report high reproducibility between replicates. Processed files, including transcript annotations in GTF, FASTA, and BED formats, are publicly available to facilitate reuse. This resource supports a wide range of downstream applications such as isoform discovery, transcriptome annotation, and integration with other omics data, offering a foundation for further exploration of transcriptomic complexity in cancer biology.
MeSH Terms
Humans; Cell Line, Tumor; Pancreatic Neoplasms; RNA-Seq; Sequence Analysis, RNA; Transcriptome; Datasets as Topic
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