【迁移】CellTypist 注释免疫细胞亚群 安装 CellTypist 配置环境 1234567891011conda create -n celltypist -c conda-forge r-base=4.1.2conda activate celltypistconda install -c conda-forge r-seurat=4.1.0 -yconda install -c conda-forge r-irkernel=1.3 -yIRkernel::installspec(name='celltypist', displayname='r-celltypist')conda install -c conda-forge scanpy=1.8.2 -y/opt/conda/envs/celltypist/bin/pip3 install celltypist -i https://pypi.tuna.tsinghua.edu.cn/simpleconda install -c conda-forge r-reticulate=1.24 -ypython3import celltypistcelltypist.models.download_models(force_update = False) 加载包 1234567Sys.setenv(RETICULATE_PYTHON = "/opt/conda/envs/celltypist/bin/python3.8")library(reticulate)scanpy = import("scanpy")celltypist = import("celltypist")pandas <- import("pandas")numpy = import("numpy")py_config() 加载数据 123library(Seurat)sce <- readRDS("~/upload/yy_zhang_data/scRNA-seq/pca.celltype.rds")Myeloid <- subset(sce, cell_type=='Myeloid') seurat 转 scanpy 123456789# 数据矩阵, scanpy与Seurat的行列定义相反adata.X = numpy$array(t(as.matrix(Myeloid[['RNA']]@counts)))# 对每个细胞的观察adata.obs = pandas$DataFrame(Myeloid@meta.data[colnames(Myeloid[['RNA']]@counts),])# 对基因矩阵的注释adata.var = pandas$DataFrame(data.frame(gene = rownames(Myeloid[['RNA']]@counts), row.names = rownames(Myeloid[['RNA']]@counts))) # 组装AnnData对象adata = scanpy$AnnData(X = adata.X, obs=adata.obs, var=adata.var) 进行预测 12345model = celltypist$models$Model$load(model = 'Immune_All_AddPIP.pkl')model$cell_typesscanpy$pp$normalize_total(adata, target_sum=1e4)scanpy$pp$log1p(adata)predictions = celltypist$annotate(adata, model = 'Immune_All_AddPIP.pkl', majority_voting = T) 预测添加到 seurat 对象 1Myeloid = AddMetaData(Myeloid, predictions$predicted_labels) #celltypist #生信 #分群 #注释 【迁移】CellTypist 注释免疫细胞亚群 https://hexo.limour.top/-qian-yi-CellTypist-zhu-shi-mian-yi-xi-bao-ya-qun Author Limour Posted on February 22, 2022 Licensed under 【迁移】STAR:一键脚本 Previous 【迁移】二代测序数据处理之数据格式说明 Next Please enable JavaScript to view the comments