Seurat Split By - Corrected Scaling

wt.subset <- subset(immune.combined, subset = stim == c("CTRL"))
ko.subset <- subset(immune.combined, subset = stim == c("Trp63-"))

FeaturePlot(immune.combined,features = c("Foxi2","Foxc1"),split.by = "stim")

gg1 <- plot_split_by_feature(wt.subset,ko.subset,c("Foxi2"))
gg2 <- plot_split_by_feature(wt.subset,ko.subset,c("Foxc1"))
ggsave(file="Foxi2_Foxc1.png",plot_grid(gg1,gg2,ncol=1))
plot_split_by_feature<- function(wildType, knockout, feature ) {
  ptSize = .4
  tmp <- data.frame("UMAP_1"= wildType@reductions$umap@cell.embeddings[,1],
                    "UMAP_2"= wildType@reductions$umap@cell.embeddings[,2],
                    LogNorm = wildType@assays$RNA@data[rownames(wildType@assays$RNA@data) %in% c(feature),])
  
  tmp2 <- data.frame("UMAP_1"= knockout@reductions$umap@cell.embeddings[,1],
                     "UMAP_2"= knockout@reductions$umap@cell.embeddings[,2],
                     LogNorm = knockout@assays$RNA@data[rownames(knockout@assays$RNA@data) %in% c(feature),])
  
  min = min(tmp$LogNorm,tmp2$LogNorm)
  max = max(tmp$LogNorm,tmp2$LogNorm)
  
  g1 <- ggplot(tmp, aes(x=UMAP_1, y=UMAP_2,colour=LogNorm)) + geom_point(size=ptSize) + theme_cowplot() +
    scale_color_gradientn(colors = c("gray","blue"),
                          limits = c(min,max)) + xlim(-13, 13) +
    ylim(-13,13) +ggtitle("Wildtype") + 
    theme(plot.title = element_text(hjust = 0.6,vjust = .2))
  
  g2 <- ggplot(tmp2, aes(x=UMAP_1, y=UMAP_2,colour=LogNorm)) + geom_point(size=ptSize) + theme_cowplot() +
    scale_color_gradientn(colors = c("gray","blue"),
                          limits = c(min,max)) + xlim(-13, 13) +
    ylim(-13,13) + ggtitle("Knockout") +
    theme(plot.title = element_text(hjust = 0.6,vjust = .2))
  
  
  plot_grid(g1,g2,labels = c(feature),label_x = .9)
}