limour-blog.github.io/source/_posts/2022-02-22-【迁移】CellTypist-注释免疫细胞亚群.md

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title: 【迁移】CellTypist 注释免疫细胞亚群 urlname: -qian-yi-CellTypist-zhu-shi-mian-yi-xi-bao-ya-qun date: 2022-02-22 13:35:24 tags: ['celltypist', '生信', '分群', '注释']

excerpt: 安装CellTypist并配置环境，加载所需的包，加载数据，将Seurat对象转换为scanpy对象，对每个细胞进行观察，对基因矩阵进行注释，组装AnnData对象，进行预测，并将预测结果添加到Seurat对象中。

安装 CellTypist

• 配置环境

  conda create -n celltypist -c conda-forge r-base=4.1.2
  conda activate celltypist
  conda install -c conda-forge r-seurat=4.1.0 -y
  conda install -c conda-forge r-irkernel=1.3 -y
  IRkernel::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/simple
  conda install -c conda-forge r-reticulate=1.24 -y
  python3
  import celltypist
  celltypist.models.download_models(force_update = False)
  

  加载包

  Sys.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

  library(Seurat)
  sce <- readRDS("~/upload/yy_zhang_data/scRNA-seq/pca.celltype.rds")
  Myeloid <- subset(sce, cell_type=='Myeloid')
  

  seurat 转 scanpy

  # 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

model = celltypist$models$Model$load(model = 'Immune_All_AddPIP.pkl')
model$cell_types
scanpy$pp$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

Myeloid = AddMetaData(Myeloid, predictions$predicted_labels)