CellMarker 3.0: an updated resource of manually curated and computationally predicted cell markers in human/mouse and...

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.