Skip to main content

MINI REVIEW article

Front. Bioinform.
Sec. Single Cell Bioinformatics
Volume 4 - 2024 | doi: 10.3389/fbinf.2024.1417428
This article is part of the Research Topic Women in Bioinformatics View all 4 articles

A Systematic Overview of Single-Cell Transcriptomics Databases, their Use cases, and Limitations

Provisionally accepted
Mahnoor N. Gondal Mahnoor N. Gondal 1,2Saad Ur Rehman Shah Saad Ur Rehman Shah 3*Arul M. Chinnaiyan Arul M. Chinnaiyan 1,2,4,5,6,7*Marcin Cieslik Marcin Cieslik 1,2,4,7*
  • 1 Department of Computational Medicine and Bioinformatics, School of Medicine, Michigan Medicine, University of Michigan, Ann Arbor, Michigan, United States
  • 2 Other, Ann Arbor, United States
  • 3 Gies College of Business, University of Illinois at Urbana–Champaign, Champaign, Illinois, United States
  • 4 Department of Pathology, School of Medicine, Michigan Medicine, University of Michigan, Ann Arbor, Michigan, United States
  • 5 Department of Urology, School of Medicine, Michigan Medicine, University of Michigan, Ann Arbor, Michigan, United States
  • 6 Howard Hughes Medical Institute (HHMI), Chevy Chase, Maryland, United States
  • 7 Rogel Cancer Center, Michigan Medicine, University of Michigan, Ann Arbor, Michigan, United States

The final, formatted version of the article will be published soon.

    Rapid advancements in high-throughput single-cell RNA-seq (scRNA-seq) technologies and experimental protocols have led to the generation of vast amounts of transcriptomic data that populates several online databases and repositories. Here, we systematically examined large-scale scRNA-seq databases, categorizing them based on their scope and purpose such as general, tissue-specific databases, disease-specific databases, cancer-focused databases, and cell type-focused databases. Next, we discuss the technical and methodological challenges associated with curating large-scale scRNA-seq databases, along with current computational solutions. We argue that understanding scRNA-seq databases, including their limitations and assumptions, is crucial for effectively utilizing this data to make robust discoveries and identify novel biological insights. Such platforms can help bridge the gap between computational and wet lab scientists through user-friendly web-based interfaces needed for democratizing access to single-cell data. These platforms would facilitate interdisciplinary research, enabling researchers from various disciplines to collaborate effectively. This review underscores the importance of leveraging computational approaches to unravel the complexities of single-cell data and offers a promising direction for future research in the field.

    Keywords: single-cell RNA-seq, Single-cell Databases, Single-cell atlases, Single-cell data analysis, Web-based platforms, Cell heterogeneity, Single-cell data integration, computational methods

    Received: 14 Apr 2024; Accepted: 11 Jun 2024.

    Copyright: © 2024 Gondal, Shah, Chinnaiyan and Cieslik. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Saad Ur Rehman Shah, Gies College of Business, University of Illinois at Urbana–Champaign, Champaign, 61820, Illinois, United States
    Arul M. Chinnaiyan, Department of Computational Medicine and Bioinformatics, School of Medicine, Michigan Medicine, University of Michigan, Ann Arbor, 48109-2218, Michigan, United States
    Marcin Cieslik, Department of Computational Medicine and Bioinformatics, School of Medicine, Michigan Medicine, University of Michigan, Ann Arbor, 48109-2218, Michigan, United States

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.