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Nucleic Acids Research·· 1 天前精选AI 评分72

CellMarker 3.0 发布:扩充细胞标志物资源并新增空间转录组分析工具

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

AI 导读

CellMarker 3.0 发布,在人工审编标志物基础上整合了算法预测的细胞类型标志物,并新增空间转录组分析模块。相比上一版本,本次新增 274 个组织、1877 种细胞类型、64 040 个标志物和 1 245 923 条组织–细胞类型–标志物条目;当前版本共收录 930 个组织、4455 种细胞类型和 90 955 个细胞标志物,条目总数达 1 329 284 条。

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来源:Nucleic Acids Research · doi.org

推荐理由

数据库新增算法预测标志物与空间转录组分析模块,做细胞类型鉴定的读者可据此了解可用资源范围。

论文摘要 · 原文

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.