Seurat-t_SEN图像优化

1、Seurat RunTSNE 参数设置

pacman::p_load(Seurat,SeuratData,dplyr,ggplot2)
data("pbmc3k")

cur_seu <- pbmc3k %>% SCTransform() %>% RunPCA() %>% FindNeighbors(dims = 1:25) %>% FindClusters(resolution = 0.3)
cur_seu <- cur_seu %>% RunTSNE(dims = 1:25,
                               perplexity = 40,     ### 参数值越大使得相同簇的空间分布更紧凑，有利于还原全局结构
                               exaggeration = 0.1)  ### 参数值越小使得全局分布更松散，视觉上更圆
DimPlot(cur_seu,reduction = 'tsne')

Reference

Parameter guide — openTSNE 1.0.0 documentation