sc.pl.umap(adata, color=['cluster', 'ptime'], legend_loc='on data') 图片.png 最后推断向量场 adata.obsm['X_VF']=tnode.get_vector_field(adata.obs['ptime'].values,adata.obsm['X_TNODE'])fig,ax=plt.subplots(ncols=1,nrows=1,figsize=(5,5))sct.vf.plot_vector_field(adata,rever...
1,umap展示某条通路的代谢得分 DimPlot.metabolism(obj = countexp.Seurat, pathway = "Glycolysis / Gluconeogenesis", dimention.reduction.type = "umap", dimention.reduction.run = F, size = 1) 2,指定通路-细胞类型点图 可以选择直接指定目标通路 或者 展示前几个,注意将phenotype 参数改为需要展示的列。
adata.obs# shows the dataframeadata.obs['sc3s_4']# returns the cluster labels The labels can then be used by subsequent functions in Scanpy, for example, plotted on UMAP and/or PCA plots. sc.pl.pca(adata,color='sc3s_4') Citation ...
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", "#F0F921FF"))) DimPlot(seurat_T, group.by = "cloneType",label = F...
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1,umap展示某条通路的代谢得分 DimPlot.metabolism(obj = countexp.Seurat,pathway ="Glycolysis / Gluconeogenesis",dimention.reduction.type="umap",dimention.reduction.run = F, size =1) 2,指定通路-细胞类型点图 可以选择直接指定目标通路 或者 展示前几个,注意将phenotype 参数改为需要展示的列。
( "embedding_keys", "annot_keys", "cluster_field", "nb_marker", "skip_matrix", "html_dir", "port", "do_debug", ) def cellbrowser( adata: AnnData, data_dir: Path | str, data_name: str, *, embedding_keys: Iterable[str] | Mapping[str, str] | str | None = None, annot_...