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December 11, 2025Frontiers in BioinformaticsOpen Access

Celline: a flexible tool for one-step retrieval and integrative analysis of public single-cell RNA sequencing data

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Authors

YSYuya SatoDokkyo UniversityTAToru AsahiWaseda UniversityKKKosuke KataokaWaseda University

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Implication

Tool streamlines data quality and quality control in single-cell RNA sequencing, enabling efficient analyses and integration.

Key Points

  • The central aim is to develop a tool for easier access and analysis of public single-cell RNA sequencing data.
  • Developed Celline as a Python package for data retrieval and analysis.
  • Utilized large language models for metadata extraction.
  • Integrated tools for quality control and batch correction.
  • Celline successfully retrieved data from public repositories and standardized metadata.
  • Achieved effective quality control and annotated major cell types.
  • Improved integration quality with a scIB score increase of +0.22.

Cite This Study

Sato et al. (2025) studied this question.

synapsesocial.com/papers/6940192a2d562116f28f6c84https://doi.org/10.3389/fbinf.2025.1684227
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Also Consider

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  1. 1SCSEQ: A web tool for analyzing single-cell RNA-seq data2026 · 1 citations
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  3. 3Advances and challenges in single-cell RNA sequencing data analysis: a comprehensive review2026 · 23 citations
  4. 4SCEMENT: Scalable and Memory Efficient Integration of Large-scale Single Cell RNA-sequencing Data2024
  5. 5scLncR: an integrated and flexible pipeline for lncRNA analysis in single-cell RNA sequencing data2026