load('data/lca_clinical.rda')
load('data/lca_cna.grch37.rda')
load('data/lca_mutations.grch37.rda')
suppressPackageStartupMessages(library(survminer))
suppressPackageStartupMessages(library(survival))
head(lca_clinical)
## patient_id histology cause_of_death time_from_surgery_to_event_months
## 1 1 2 3 6.50
## 2 3 2 2 88.47
## 3 4 1 2 27.57
## 4 6 1 <NA> 135.83
## 5 7 1 3 79.67
## 6 8 1 1 135.63
## status_dfs lung_event time_to_death_months egfr_status_diagnostic
## 1 1 0 6.50 ND
## 2 1 1 89.57 WT
## 3 1 1 47.87 WT
## 4 0 0 135.83 <NA>
## 5 1 0 79.67 WT
## 6 0 0 135.63 WT
## kras_status_diagnostic OUS_sample_id stage tobacco gender
## 1 ND 001T 2 3 1
## 2 WT 003T 1 2 1
## 3 ND 004T 3 2 2
## 4 WT <NA> NA NA NA
## 5 WT <NA> 3 2 1
## 6 G12C 008T 1 2 1
## tobacco_pack_years age tumor_size_cm KRAS
## 1 48.00 79.7 3.0 WildType
## 2 52.00 74.7 1.2 WildType
## 3 27.75 55.0 1.8 WildType
## 4 NA NA NA WildType
## 5 45.75 71.1 5.0 WildType
## 6 24.00 47.8 0.9 G12
R Markdown
library(survminer)
library(survival)
smokers <- dplyr::filter(lca_clinical, tobacco == 2 | tobacco == 3)
nonsmokers <- dplyr::filter(lca_clinical, tobacco == 1)
fit <- survfit(Surv(time_to_death_months, status_dfs) ~ KRAS, data = lca_clinical)
ggsurvplot(fit, data = lca_clinical, pval = T)
fit2 <- survfit(Surv(time_to_death_months, status_dfs) ~ egfr_status_diagnostic, data = lca_clinical)
ggsurvplot(fit2, data = lca_clinical, pval = T)
