ArticleJournal of advanced research2025
Systematic evaluation of single-cell RNA-seq analyses performance based on long-read sequencing platforms.
Article in Journal of advanced research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Single-cell RNA sequencing unravels mosquito biology and host-pathogen interactions.Parasites & vectors · 2026Review
- A systematic benchmark of bioinformatics methods for single-cell and spatial RNA-seq nanopore long reads data.NAR genomics and bioinformatics · 2026Article
- Nanopore direct RNA sequencing and the epitranscriptome: Advances in mapping native RNA landscapes.iMeta · 2026Review
- Annotating genomes at increased scale and resolution.Nature reviews. Genetics · 2026Review
- Review
- Decoding the human PBMC isonome: isoform-level resolution with single-cell long-read transcriptomics.Frontiers in genetics · 2026Article
- Bioinformatics frameworks for single-cell long-read sequencing: unlocking isoform-level resolution.Briefings in bioinformatics · 2025Review
- Comparison of single-cell long-read and short-read transcriptome sequencing via cDNA molecule matching: quality evaluation of the MAS-ISO-seq approach.NAR genomics and bioinformatics · 2025Article
- Long and Accurate: How HiFi Sequencing is Transforming Genomics.Genomics, proteomics & bioinformatics · 2025Review
- Isoform-resolution single-cell RNA sequencing reveals the transcriptional panorama of adult Baoshan pig testis cells.BMC genomics · 2025Article
- Detection of mRNA Transcript Variants.Genes · 2025Review
- Single-cell RNA sequencing in studies of type 1 diabetes mellitus: modern state-of-the-art and technical peculiarities.Frontiers in endocrinology · 2025Review
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionThe rapid development of next-generation sequencing (NGS)-based single-cell RNA sequencing (scRNA-seq) allows for detecting and quantifying gene expression in a high-throughput manner, providing a powerful tool for comprehensively understanding cellular function in various biological processes. However, the NGS-based scRNA-seq only quantifies gene expression and cannot reveal the exact transcript structures (isoforms) of each gene due to the limited read length. On the other hand, the long read length of third-generation sequencing (TGS) technologies, including Oxford Nanopore Technologies (ONT) and Pacific Biosciences (PacBio), enable direct reading of intact cDNA molecules.
objectivesBoth ONT and PacBio have been used in conjunction with scRNA-seq, but their performance in single-cell analyses has not been systematically evaluated.
methodsTo address this, we generated ONT and PacBio data from the same single-cell cDNA libraries containing different amount of cells.
resultsUsing NGS as a control, we assessed the performance of each platform in cell type identification. Additionally, the reliability in identifying novel isoforms and allele-specific gene/isoform expression by both platforms was verified, providing a systematic evaluation to design the sequencing strategies in single-cell transcriptome studies.
conclusionBeyond gene expression analysis, which the NGS-based scRNA-seq only affords, TGS-based scRNA-seq achieved gene splicing analyses, identifying novel isoforms. Attribute to higher sequencing quality of PacBio, it outperforms ONT in accuracy of novel transcripts identification and allele-specific gene/isoform expression.
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