空转分析代码备忘录：seurat可视化代码雕琢

suppressPackageStartupMessages({    library(Seurat)    library(ggplot2)    library(viridis)    library(patchwork)    library(RColorBrewer)})
# 读取数据rds <- readRDS('./mouse_brain_sto.rds')

options(repr.plot.width=7, repr.plot.height=4)
p1 <- SpatialFeaturePlot(rds, features = "nCount_Spatial")p2 <- p1 + theme_gray()+xlab("")+ylab("")+theme(axis.text = element_blank(),axis.ticks=element_blank())
p1+p2

p1 <- SpatialDimPlot(rds)p2 <- SpatialDimPlot(rds, stroke=NA) p2 <- p2 + guides(color=guide_legend(override.aes = list(size=8), ncol=2))p2 <- p2 + theme_gray()+xlab("")+ylab("")p2 <- p2 + theme(axis.text = element_blank(),axis.ticks=element_blank())
p1+p2

spatial_corr <- rds@images$slice1@coordinates[,c('col', 'row')]colnames(spatial_corr) <- c('s_1', 's_2')spatial_corr <- as.matrix(spatial_corr)rds[["spatial"]] <- CreateDimReducObject(embeddings=spatial_corr, key = "s_", assay = "Spatial")
options(repr.plot.width=10.5, repr.plot.height=4)
p1 <- FeaturePlot(rds, features = "nCount_Spatial", reduction='spatial') +     scale_y_reverse() +     scale_colour_viridis(option="inferno") + theme_void()p2 <- FeaturePlot(rds, features = "Neurod6", reduction='spatial') +    scale_y_reverse() +     scale_colour_viridis(option="D") + theme_void()
mycolor <- colorRampPalette(brewer.pal(8,'Set2'))(18)
p3 <- DimPlot(rds, reduction='spatial', cols=mycolor) +     guides(color=guide_legend(override.aes = list(size=6), ncol=2)) +    theme_void() + scale_y_reverse()
p1+p2+p3+plot_layout(ncol=3, nrow=1)

suppressPackageStartupMessages({    library(Seurat)    library(ggplot2)    library(viridis)    library(patchwork)    library(RColorBrewer)    library(paletteer)})
Newf <- function(RDS, feature, ad=1, limits=1){    viridis_plasma_light_high <- as.vector(x = paletteer_c(palette = "viridis::inferno", n = 250, direction = 1))    viridis_plasma_light_high <- c( rep("black", ad), viridis_plasma_light_high)
    p <- FeaturePlot(RDS, features = feature, reduction='spatial')    p <- p + theme_void()+ theme(                axis.ticks=element_blank(),                axis.text.x = element_blank(),                axis.text.y = element_blank(),                axis.line = element_blank(),                panel.border = element_rect(color = "white", fill = NA, size =2),            ) +         DarkTheme() +        xlab(NULL) +         ylab(NULL)    if (length(limits)==1){        p <- p + scale_colour_gradientn(colours=viridis_plasma_light_high, na.value = "black")     }else{        p <- p + scale_colour_gradientn(colours=viridis_plasma_light_high, na.value = "black",limits=limits)    }
    return (p)}
# 读取下载的数据ca <- readRDS('spatial.rds')
p1 <- Newf(ca, "CD4 T")p2 <- Newf(ca, "CD8 T")p3 <- Newf(ca, "B")p4 <- Newf(ca, "DC")p5 <- Newf(ca, "Macro")p6 <- Newf(ca, "Endothelial")p7 <- Newf(ca, "Fibroblast")p8 <- Newf(ca, "Program_C6")p9 <- Newf(ca, "Program_C7")
options(repr.plot.width=8.5, repr.plot.height=10)p <- p1+p2+p3+p4+p5+p6+p7+p8+p9 + plot_layout(ncol=3, nrow=3)p#ggsave("out.pdf", p, w=8.5, h=10)