CellMarker 3.0: an updated resource of manually curated and computationally predicted cell markers in human/mouse and interactive web tools for single-cell and spatial transcriptomics analysis

Clicks: 11
ID: 337403
2026
Free PDF
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Emerging

Ranked #1,216 of 1,295 articles by views in Nucleic Acids Research

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 1,295 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
The updated CellMarker 3.0 resource (http://bio-bigdata.hrbmu.edu.cn/CellMarker) offers a comprehensive resource, integrating experimentally validated and robustly algorithm-predicted marker genes for diverse cell types across human and mouse tissues. In addition, web tools for analyzing single-cell RNA-seq (scRNA-seq) and spatial transcriptomics (ST) data are described. CellMarker 3.0 was updated with more data and new features, including (i) appending 274 tissues, 1877 cell types, 64 040 markers, and 1 245 923 tissue-cell type-marker entries over the previous version. The current release contains 930 tissues, 4455 cell types, and 90 955 cell markers, resulting in a total of 1 329 284 tissue-cell type-marker entries. (ii) Expanding the resource to include computationally predicted cell-type markers derived from six algorithms, namely Spapros, Seurat::FindAllMarkers, SEMITONES, Cepo, CelliD, and COSG. (iii) New marker information was incorporated from 168 sequencing technologies, such as CEL-Seq2 and SNARE-seq. (iv) Covering 35 types of cell markers, including protein-coding genes, rRNAs, and pseudogenes. (v) The cell tool module was comprehensively restructured and upgraded, with the original six scRNA-seq analysis modules systematically optimized and two new spatial transcriptomics modules, Spatial Expression, and Spatial Chat, added. CellMarker 3.0 is a valuable resource that integrates cell identity identification, single-cell transcriptomics, and spatial transcriptomics analysis.
Reference Key
openalex_W7223949284 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Congxue Hu, Tengyue Li, Minghui Zhu, Liyuan Li, Bolin Ren, Kuan Yang, Zhenzhen Wang, Maohao Li, Baobin Qi, Yongjin Long, Na Lv, X. Yang, Rui Fu, Jing Bai, Xia Li, Yunpeng Zhang
Are you one of these authors? Claim your profile
Journal Nucleic Acids Research
Year 2026
DOI
10.1093/nar/gkag1040
URL
https://doi.org/10.1093/nar/gkag1040
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.