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Script/Figure_5c_6a_6d.R

+library(Seurat)
+library(stringr)
+library(ggplot2)
+library(openxlsx)
+library(ggpubr)
+
+#import metadata from  Excel file
+Seurat_metadata <- "SingleCell_seurat_metadata.xlsx"
+t <- read.xlsx(xlsxFile = Seurat_metadata, sheet = "metadata_Teff_memcells")
+
+# Extract relevant columns for each score analysed (e.g, Activation, Exhaustion, SASP)
+t_activation_filt <- t[,c("RNA_Group", "Cluster", "Activation Score1")]
+t_sasp_filt <- t[,c("RNA_Group", "Cluster", "SASP Score1")]
+t_exhaustion_filt <- t[,c("RNA_Group", "Cluster", "Exhaustion_Score1")]
+
+
+# Create the activation score plot + ANOVA and T test statistic (exact pvalue)
+activation_score_plot<- ggplot(data = t_filt, mapping = aes(x = RNA_Group, y = Activation_Score1, fill = RNA_Group)) + #color = RNA_Group
+  theme_bw(base_size = 16) +
+  theme(legend.position = "none") +
+  xlab("") +
+  labs(title="", y="Activation Score", fill="Condition")+
+  geom_boxplot(alpha = .5, outlier.size = 0) +
+  scale_fill_manual(values = c("FER" = "lightgrey", "OAT" = "khaki", "NOA" = "dodgerblue"))+
+  facet_grid(.~Cluster) + #switch = "x"
+  stat_compare_means(method = "anova", label.y = 0.45) +
+  stat_compare_means(comparisons = list(c("NOA", "OAT"), c("FER", "OAT"),c("FER", "NOA")), exact=T, method = "t.test",tip.length = 0.01, bracket.size = 0.5,
+                     p.adjust.method = "bonferroni", label = "p.format", label.y = c(0.30, 0.35, 0.40))  
+
+# Save the plot as a PDF
+pdf(file = "activation_score_exact_value.pdf", width = 16, height = 6)
+activation_score_plot
+dev.off()
+
+
+# Create the exhaustion score plot + ANOVA and T test statistic (exact pvalue)
+exhaustion_score_plot <-ggplot(data = t_exhaustion_filt, mapping = aes(x = RNA_Group, y = Exhaustion_Score1, fill = RNA_Group)) + #color = RNA_Group
+  theme_bw(base_size = 16) +
+  theme(legend.position = "none") +
+  xlab("") +
+  labs(title="", y="Exhaustion Score", fill="Condition")+
+  geom_boxplot(alpha = .5, outlier.size = 0) +
+  scale_fill_manual(values = c("FER" = "lightgrey", "OAT" = "khaki", "NOA" = "dodgerblue"))+
+  facet_grid(.~Cluster) + #switch = "x"
+  stat_compare_means(method = "anova", label.y = 0.85) +
+  stat_compare_means(comparisons = list(c("NOA", "OAT"), c("FER", "OAT"),c("FER", "NOA")), exact=T, method = "t.test",tip.length = 0.01, bracket.size = 0.5,
+                     p.adjust.method = "bonferroni", label = "p.format", label.y = c(0.50, 0.60, 0.70)) 
+
+# Save the plot as a PDF
+pdf(file = "exhaustion_score_exact_value.pdf", width = 16, height = 6)
+exhaustion_score_plot
+dev.off()
+
+# Create the sasp score plot + ANOVA and T test statistic (exact pvalue)
+sasp_activation_score_plot<- ggplot(data = t_sasp_filt, mapping = aes(x = RNA_Group, y = SASP_Score1, fill = RNA_Group)) + #color = RNA_Group
+  theme_bw(base_size = 16) +
+  theme(legend.position = "none") +
+  xlab("") +
+  labs(title="", y="SASP Score", fill="Condition")+
+  geom_boxplot(alpha = .5, outlier.size = 0) +
+  scale_fill_manual(values = c("FER" = "lightgrey", "OAT" = "khaki", "NOA" = "dodgerblue"))+
+  facet_grid(.~Cluster) + #switch = "x"
+  stat_compare_means(method = "anova", label.y = 0.75) +
+  stat_compare_means(comparisons = list(c("NOA", "OAT"), c("FER", "OAT"),c("FER", "NOA")), exact=T, method = "t.test",tip.length = 0.01, bracket.size = 0.5,
+                     p.adjust.method = "bonferroni", label = "p.format", label.y = c(0.45, 0.55, 0.65)) 
+
+# Save the plot as a PDF
+pdf(file = "sasp_score_exact_value.pdf", width = 16, height = 6)
+sasp_activation_score_plot
+dev.off()
+