#ADENO SURVIVAL

library(survival)
library(survminer)
## Loading required package: ggplot2
## Loading required package: ggpubr
## 
## Attaching package: 'survminer'
## The following object is masked from 'package:survival':
## 
##     myeloma
ADENO_SURVIVAL <- readRDS("~/YEPYENI/ennnn_clinic_adeno.rds")
data <- ADENO_SURVIVAL
data$overall_survival <- as.numeric(data$overall_survival)

cDC1

res.cut <- surv_cutpoint(data, time = "overall_survival", event = "deceased",
                         variables = c("cDC1"))
cutpoint <- res.cut[["cutpoint"]][["cutpoint"]]
data$cdc1 <- ifelse(data$`cDC1` > cutpoint, "HIGH", "LOW")
fit_cdc1 <- survfit(Surv(overall_survival, deceased) ~ cdc1, data = data)
ggsurvplot(fit_cdc1,
           data,
           pval = TRUE,
           risk.table = TRUE)

print(ggsurvplot(fit_cdc1, data, pval = TRUE, risk.table = TRUE))

cDC2

res.cut <- surv_cutpoint(data, time = "overall_survival", event = "deceased",
                         variables = c("cDC2"))
cutpoint <- res.cut[["cutpoint"]][["cutpoint"]]
data$cdc2 <- ifelse(data$cDC2 > cutpoint, "HIGH", "LOW")
fit_cdc2 <- survfit(Surv(overall_survival, deceased) ~ cdc2, data = data)
ggsurvplot(fit_cdc2,
           data,
           pval = TRUE,
           risk.table = TRUE)

print(ggsurvplot(fit_cdc2, data, pval = TRUE, risk.table = TRUE))

#pDC

res.cut <- surv_cutpoint(data, time = "overall_survival", event = "deceased",
                         variables = c("pDC"))
cutpoint <- res.cut[["cutpoint"]][["cutpoint"]]
data$pdc <- ifelse(data$pDC > cutpoint, "HIGH", "LOW")
fit_pdc <- survfit(Surv(overall_survival, deceased) ~ pdc, data = data)
ggsurvplot(fit_pdc, data, pval = TRUE, risk.table = TRUE)

DC mature

res.cut <- surv_cutpoint(data, time = "overall_survival", event = "deceased",
                         variables = c("DC mature"))
cutpoint <- res.cut[["cutpoint"]][["cutpoint"]]
data$dcmature <- ifelse(data$`DC mature` > cutpoint, "HIGH", "LOW")
fit_dcmature <- survfit(Surv(overall_survival, deceased) ~ dcmature, data = data)
ggsurvplot(fit_dcmature, data, pval = TRUE, risk.table = TRUE)

Macrophage

res.cut <- surv_cutpoint(data, time = "overall_survival", event = "deceased",
                         variables = c("Macrophage"))
cutpoint <- res.cut[["cutpoint"]][["cutpoint"]]
data$macrophage <- ifelse(data$Macrophage > cutpoint, "HIGH", "LOW")
fit_macrophage <- survfit(Surv(overall_survival, deceased) ~ macrophage, data = data)
ggsurvplot(fit_macrophage, data, pval = TRUE, risk.table = TRUE)

Macrophage alveolar

res.cut <- surv_cutpoint(data, time = "overall_survival", event = "deceased",
                         variables = c("Macrophage alveolar"))
cutpoint <- res.cut[["cutpoint"]][["cutpoint"]]
data$macrophage_alveolar <- ifelse(data$`Macrophage alveolar` > cutpoint, "HIGH", "LOW")
fit_macrophage_alveolar <- survfit(Surv(overall_survival, deceased) ~ macrophage_alveolar, data = data)
ggsurvplot(fit_macrophage_alveolar, data, pval = TRUE, risk.table = TRUE)

Monocyte classical

#res.cut <- surv_cutpoint(data, time = "overall_survival", event = "deceased",
#                         variables = c("Monocyte classical"))
#cutpoint <- res.cut[["cutpoint"]][["cutpoint"]]
#data$monocyte_classical <- ifelse(data$`Monocyte classical` > cutpoint, "HIGH", "LOW")
#fit_monocyte_classical <- survfit(Surv(overall_survival, deceased) ~ monocyte_classical, data = data)
#ggsurvplot(fit_monocyte_classical, data, pval = TRUE, risk.table = TRUE)

Monocyte non-classical

res.cut <- surv_cutpoint(data, time = "overall_survival", event = "deceased",
                         variables = c("Monocyte non-classical"))
cutpoint <- res.cut[["cutpoint"]][["cutpoint"]]
data$monocyte_non_classical <- ifelse(data$`Monocyte non-classical` > cutpoint, "HIGH", "LOW")
fit_monocyte_non_classical <- survfit(Surv(overall_survival, deceased) ~ monocyte_non_classical, data = data)
ggsurvplot(fit_monocyte_non_classical, data, pval = TRUE, risk.table = TRUE)

Myeloid dividing

res.cut <- surv_cutpoint(data, time = "overall_survival", event = "deceased",
                         variables = c("Myeloid dividing"))
cutpoint <- res.cut[["cutpoint"]][["cutpoint"]]
data$myeloid_dividing <- ifelse(data$`Myeloid dividing` > cutpoint, "HIGH", "LOW")
fit_myeloid_dividing <- survfit(Surv(overall_survival, deceased) ~ myeloid_dividing, data = data)
ggsurvplot(fit_myeloid_dividing, data, pval = TRUE, risk.table = TRUE)

Neutrophils

res.cut <- surv_cutpoint(data, time = "overall_survival", event = "deceased",
                         variables = c("Neutrophils"))
cutpoint <- res.cut[["cutpoint"]][["cutpoint"]]
data$neutrophils <- ifelse(data$Neutrophils > cutpoint, "HIGH", "LOW")
fit_neutrophils <- survfit(Surv(overall_survival, deceased) ~ neutrophils, data = data)
ggsurvplot(fit_neutrophils, data, pval = TRUE, risk.table = TRUE)

Plasma cell için işlem

res.cut <- surv_cutpoint(data, time = "overall_survival", event = "deceased",
                         variables = c("Plasma cell"))
cutpoint <- res.cut[["cutpoint"]][["cutpoint"]]
data$plasma_cell <- ifelse(data$`Plasma cell` > cutpoint, "HIGH", "LOW")
fit_plasma_cell <- survfit(Surv(overall_survival, deceased) ~ plasma_cell, data = data)
ggsurvplot(fit_plasma_cell, data, pval = TRUE, risk.table = TRUE)

Plasma cell dividing için işlem

res.cut <- surv_cutpoint(data, time = "overall_survival", event = "deceased",
                         variables = c("Plasma cell dividing"))
cutpoint <- res.cut[["cutpoint"]][["cutpoint"]]
data$plasma_cell_dividing <- ifelse(data$`Plasma cell dividing` > cutpoint, "HIGH", "LOW")
fit_plasma_cell_dividing <- survfit(Surv(overall_survival, deceased) ~ plasma_cell_dividing, data = data)
ggsurvplot(fit_plasma_cell_dividing, data, pval = TRUE, risk.table = TRUE)

#Pericyte

res.cut <- surv_cutpoint(data, time = "overall_survival", event = "deceased",
                         variables = c("Pericyte"))
cutpoint <- res.cut[["cutpoint"]][["cutpoint"]]
data$pericyte <- ifelse(data$Pericyte > cutpoint, "HIGH", "LOW")
fit_pericyte <- survfit(Surv(overall_survival, deceased) ~ pericyte, data = data)
ggsurvplot(fit_pericyte, data, pval = TRUE, risk.table = TRUE)

T cell CD4

res.cut <- surv_cutpoint(data, time = "overall_survival", event = "deceased",
                         variables = c("T cell CD4"))
cutpoint <- res.cut[["cutpoint"]][["cutpoint"]]
data$t_cell_cd4 <- ifelse(data$`T cell CD4` > cutpoint, "HIGH", "LOW")
fit_t_cell_cd4 <- survfit(Surv(overall_survival, deceased) ~ t_cell_cd4, data = data)
ggsurvplot(fit_t_cell_cd4, data, pval = TRUE, risk.table = TRUE)

#res.cut <- surv_cutpoint(data, time = "overall_survival", event = "deceased",
#                        variables = c("T CD4 dividing"))
#cutpoint <- res.cut[["cutpoint"]][["cutpoint"]]
#data$t_cell_cd4_dividing <- ifelse(data$`T cell CD4 dividing` > cutpoint, "HIGH", "LOW")
#fit_t_cell_cd4_dividing <- survfit(Surv(overall_survival, deceased) ~ t_cell_cd4_dividing, data = data)
#ggsurvplot(fit_t_cell_cd4_dividing, data, pval = TRUE, risk.table = TRUE)

T cell CD8 activated

res.cut <- surv_cutpoint(data, time = "overall_survival", event = "deceased",
                         variables = c("T cell CD8 activated"))
cutpoint <- res.cut[["cutpoint"]][["cutpoint"]]
data$t_cell_cd8_activated <- ifelse(data$`T cell CD8 activated` > cutpoint, "HIGH", "LOW")
fit_t_cell_cd8_activated <- survfit(Surv(overall_survival, deceased) ~ t_cell_cd8_activated, data = data)
ggsurvplot(fit_t_cell_cd8_activated, data, pval = TRUE, risk.table = TRUE)

T cell CD8 dividing

res.cut <- surv_cutpoint(data, time = "overall_survival", event = "deceased",
                         variables = c("T cell CD8 dividing"))
cutpoint <- res.cut[["cutpoint"]][["cutpoint"]]
data$t_cell_cd8_dividing <- ifelse(data$`T cell CD8 dividing` > cutpoint, "HIGH", "LOW")
fit_t_cell_cd8_dividing <- survfit(Surv(overall_survival, deceased) ~ t_cell_cd8_dividing, data = data)
ggsurvplot(fit_t_cell_cd8_dividing, data, pval = TRUE, risk.table = TRUE)

#T cell CD8 effector memory

res.cut <- surv_cutpoint(data, time = "overall_survival", event = "deceased",
                         variables = c("T cell CD8 effector memory"))
cutpoint <- res.cut[["cutpoint"]][["cutpoint"]]
data$t_cell_cd8_effector_memory_acl <- ifelse(data$`T cell CD8 effector memory` > cutpoint, "HIGH", "LOW")
fit_t_cell_cd8_effector_memory_acl <- survfit(Surv(overall_survival, deceased) ~ t_cell_cd8_effector_memory_acl, data = data)

ggsurvplot(fit_t_cell_cd8_effector_memory_acl, data, pval = TRUE, risk.table = TRUE)

T cell CD8 terminally exhausted

res.cut <- surv_cutpoint(data, time = "overall_survival", event = "deceased",
                         variables = c("T cell CD8 terminally exhausted"))
cutpoint <- res.cut[["cutpoint"]][["cutpoint"]]
data$t_cell_cd8_terminally_exhausted <- ifelse(data$`T cell CD8 terminally exhausted` > cutpoint, "HIGH", "LOW")
fit_t_cell_cd8_terminally_exhausted <- survfit(Surv(overall_survival, deceased) ~ t_cell_cd8_terminally_exhausted, data = data)
ggsurvplot(fit_t_cell_cd8_terminally_exhausted, data, pval = TRUE, risk.table = TRUE)

#T cell CD8 naive

#res.cut <- surv_cutpoint(data, time = "overall_survival", event = "deceased",
#                         variables = c("T cell CD8 naive"))
#cutpoint <- res.cut[["cutpoint"]][["cutpoint"]]
#data$t_cell_cd8_naive <- ifelse(data$`T cell CD8 naive` > cutpoint, "HIGH", "LOW")
#fit_t_cell_cd8_naive <- survfit(Surv(overall_survival, deceased) ~ t_cell_cd8_naive, data = data)
#ggsurvplot(fit_t_cell_cd8_naive, data, pval = TRUE, risk.table = TRUE)

T cell NK-like

res.cut <- surv_cutpoint(data, time = "overall_survival", event = "deceased",
                         variables = c("T cell NK-like"))
cutpoint <- res.cut[["cutpoint"]][["cutpoint"]]
data$t_cell_nk_like <- ifelse(data$`T cell NK-like` > cutpoint, "HIGH", "LOW")
fit_t_cell_nk_like <- survfit(Surv(overall_survival, deceased) ~ t_cell_nk_like, data = data)
ggsurvplot(fit_t_cell_nk_like, data, pval = TRUE, risk.table = TRUE)

T cell regulatory

res.cut <- surv_cutpoint(data, time = "overall_survival", event = "deceased",
                         variables = c("T cell regulatory"))
cutpoint <- res.cut[["cutpoint"]][["cutpoint"]]
data$t_cell_regulatory <- ifelse(data$`T cell regulatory` > cutpoint, "HIGH", "LOW")
fit_t_cell_regulatory <- survfit(Surv(overall_survival, deceased) ~ t_cell_regulatory, data = data)
ggsurvplot(fit_t_cell_regulatory, data, pval = TRUE, risk.table = TRUE)