# Plot IHC percentages of VISTA+ cells in different hematological cancers (Figure 5F)

library(data.table)

library(ggplot2)

library(cowplot)

library(ComplexHeatmap)

library(dplyr)

library(ggpubr)

# read mIHC data

data <- fread("vista_ihc.txt", data.table = F)

# prepare data frame for plotting

df <- data %>%

  mutate(Disease_2 = gsub("BP CML", "CML", 

                          gsub("PH. B-ALL", "pre-B-ALL", 

                               gsub("HB", "Healthy BM", Disease))),

         VISTA = VISTA.fraction*100) %>%

  mutate(Disease_2 = ifelse(FAB %in% c("4", "5"), "AML M4/M5", 

                            ifelse(Disease_2 == "AML", "AML other", Disease_2))) %>% 

  mutate(Disease_2 = factor(Disease_2, levels = c("AML M4/M5", "AML other", "CML", "pre-B-ALL", "T-ALL", "Healthy BM")))

# boxplot

p <- ggplot(df, aes(x=Disease_2, y=VISTA, fill = Disease_2)) +

 geom_boxplot(outlier.shape = NA) +

 geom_jitter(width = 0.1, color = "grey20") +

 scale_size_continuous(range = c(0.1, 2)) +

 ylab("% VISTA+ cells") +

 xlab("") +

 guides(fill = FALSE) +

  theme_cowplot() +

 theme(axis.text.x = element_text(angle=45, hjust=1)) +

 labs(color = "") +

 stat_compare_means(aes(label = ..p.signif..),

   method = "wilcox.test",

   method.args = list(alternative = "two.sided"),

   ref.group = "Healthy BM",

   label.y = 95)

# print

pdf("Figure5F_VISTA_IHC_boxplot.pdf", width = 3, height = 4)

p

dev.off()