diff --git a/Clustering_Analysis/Paper_figures.R b/Clustering_Analysis/Paper_figures.R
index e2242b17dc7de7f2f39092accb2d53e1b815cef7..365a95b5626d0d3d8944ba0c782a8f00aea20f94 100644
--- a/Clustering_Analysis/Paper_figures.R
+++ b/Clustering_Analysis/Paper_figures.R
@@ -41,3 +41,31 @@ p_m <- ggplot(data = df_m, mapping = aes(x = UMAPh_1, y = UMAPh_2, color = Annot
   geom_point(size = .6)
 Seurat::LabelClusters(plot = p_m, id = "Annotation", color = "black", size = 5)
 
+# Figure S12 - CD4 CAR-T
+df$CART_CD4_MAGIC[is.na(df$CART_CD4_MAGIC)] <- "NOCAR"
+t <- table(df$CART_CD4_MAGIC, df$orig.ident)
+t <- rbind(t, colSums(t))
+rownames(t) <- c("CART_CD4_MAGIC", "NOCAR", "Total")
+t <- data.frame(t(t))
+t$CART_CD4_MAGIC_perc <- 100 * (t$CART_CD4_MAGIC / t$Total)
+t$Condition <- stringr::str_split_fixed(rownames(t), "-", 2)[,2]
+
+# Fig. S12 - A
+ggplot(data = t, mapping = aes(x = Condition, y = CART_CD4_MAGIC_perc, color = Condition)) +
+  theme_bw(base_size = 18) +
+  theme(legend.position = "none") +
+  geom_point(size = 3) +
+  ylab("CD4 WPRE+ (% of total cells)") +
+  xlab("") +
+  scale_y_continuous(limits = c(0,6))
+
+# Fig. S12 - B
+t <- df %>% filter(CART_CD4_MAGIC == "CART_CD4_MAGIC") %>%
+  group_by(PROP.Condition, Annotation) %>%
+  summarise(TotCells = n())
+ggplot(data = t, mapping = aes(x = PROP.Condition, y = TotCells, fill = Annotation)) +
+  theme_bw(base_size = 18) +
+  theme(legend.position = "right") +
+  geom_bar(stat = "identity", position = "fill") +
+  xlab("") +
+  ylab("count")