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 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.

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Publication Details

Journal
Scientific Data
Published
2025-10-20
DOI
https://doi.org/10.1038/s41597-025-05939-0
Citations
1
Primary Topic
Cancer Genomics and Diagnostics
Type
article
Field-Weighted Citation Impact
0.94

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article

Long-read RNA sequencing dataset of human pancreatic cancer cell lines

Jiling Feng, Shengli Li, Yu Zeng, Hao Wu et al.
1 citations
Scientific Data
Cancer Genomics and Diagnostics
0.94
article

Long-read RNA sequencing dataset of human pancreatic cancer cell lines

Jiling Feng, Shengli Li, Yu Zeng, Hao Wu, Shengnan Luo, Yingxia Zheng
article en
1 citations

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.

Scientific DataVol. 12(1)
Shanghai Jiao Tong University (CN), XinHua Hospital (CN), Shanghai Ninth People's Hospital (CN)
Shanghai Rising-Star Program
Openalex Percentile: Top 19%
Cancer Genomics and Diagnostics
0.94
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