Centre de Recherches en Cancérologie de Toulouse, INSERM UMR1037, Toulouse, France.
Université Toulouse III Paul-Sabatier, Toulouse, France.
Nucleic Acids Res. 2019 Dec 2;47(21):e133. doi: 10.1093/nar/gkz601.
The momentum of scRNA-seq datasets prompts for simple and powerful tools exploring their meaningful signatures. Here we present Single-Cell_Signature_Explorer (https://sites.google.com/site/fredsoftwares/products/single-cell-signature-explorer), the first method for qualitative and high-throughput scoring of any gene set-based signature at the single cell level and its visualization using t-SNE or UMAP. By scanning datasets for single or combined signatures, it rapidly maps any multi-gene feature, exemplified here with signatures of cell lineages, biological hallmarks and metabolic pathways in large scRNAseq datasets of human PBMC, melanoma, lung cancer and adult testis.
单细胞测序数据集的发展趋势迫切需要简单而强大的工具来探索其有意义的特征。这里我们介绍单细胞特征探索器(Single-Cell_Signature_Explorer,https://sites.google.com/site/fredsoftwares/products/single-cell-signature-explorer),这是第一个能够在单细胞水平上对任何基于基因集的特征进行定性和高通量评分的方法,并且可以使用 t-SNE 或 UMAP 进行可视化。通过扫描数据集的单个或组合特征,它可以快速映射任何多基因特征,这里通过人类 PBMC、黑色素瘤、肺癌和成人睾丸的大型 scRNAseq 数据集展示了细胞谱系、生物学标志和代谢途径的特征。