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
Congxue Hu, Tengyue Li, Minghui Zhu, Liyuan Li, Bolin Ren, Kuan Yang, Zhenzhen Wang, Maohao Li, Baobin Qi, Yongjin Long, Na Lv, Xiaoxu Yang, Rui Fu, Jing Bai, Xia Li, Yunpeng ZhangAbstract
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.