sc.pl.umap(adata_embds,color=["cell_type_from_scMulan","cell_type_from_mulan_smoothing",'cell_type'],ncols=1) sc.pl.umap(adata_embds, color = ['batch']) [1] Haiyang Bian, Yixin Chen, Xiaomin Dong, Chen Li, Minsheng Hao, Sijie Chen, Jinyi Hu, Maosong Sun, Lei Wei, Xuegong...
'leiden_res0_5_colors', 'leiden_res1_colors', 'manual_celltype_annotation_colors', 'neighbors', 'pca', 'phase_colors', 'replicate_colors', 'tsne', 'umap', 'schist', 'nsbm_level_1_colors', 'nsbm_level_2_colors'
#dittoScatterPlot()的轴是基因表达数据或meta数据,dittoDimPlot()的轴是降维,如 tsne、pca、umap 或类似数据dittoScatterPlot(object=sce,x.var="nCount_RNA",y.var="nFeature_RNA",color.var="percent.mito")dittoDimPlot(sce,"cluster",do.label=TRUE,labels.repel=FALSE,add.trajectory.lineages=list(c("...
load("combined_seurat_T.RData")head(seurat_T,2) 二scRepertoire可视化 使用常规方式在umap图中展示cloneType的信息 colorblind_vector <- colorRampPalette(rev(c("#0D0887FF", "#47039FFF","#7301A8FF", "#9C179EFF","#BD3786FF", "#D8576BFF","#ED7953FF","#FA9E3BFF","#FDC926FF", "#...
(adata_t, use_rep="X_scGPT") sc.tl.umap(adata_t, min_dist=0.3) fig = sc.pl.umap( adata_t, color=["celltype"], title=[ f"celltype, avg_bio = {results.get('avg_bio', 0.0):.4f}", ], frameon=False, return_fig=True, show=False, ) results["celltype_umap"] = fig if...
Visualize annotation present in `adata`. By default, export all gene expression data from `adata.raw` and categorical and continuous annotations present in `adata.obs`. See `SPRING <https://github.com/AllonKleinLab/SPRING>`__ or [Weinreb17]_ for details. Parameters --- adata Annotated data...