Survival function with dropdown menu for each gene - r

Question

I am trying to make a shiny app where you can select different miRNA in my input then plot the survival curve using ggsurvplot. There is something wrong with the functions within fitSurv, but I am not sure where I am doing it wrong.
library(dplyr)
require(survminer)
library(tidyverse)
require(reshape2)
library(shiny)
library(tidyr)
require(survival)
example data:
df.miRNA.cpm <- structure(list(`86` = c(5.57979757386892, 17.0240095264258, 4.28380151026145,
13.0457611762755, 12.5531123449841), `175` = c(5.21619202802748,
15.2849097474841, 2.46719979911461, 10.879496005461, 9.66416497290915
), `217` = c(5.42796072966512, 17.1413407297933, 5.15230233060323,
12.2646127361351, 12.1031024927547), `394` = c(-1.1390337316217,
15.1021660424984, 4.63168157763046, 11.1299079134792, 9.55572588729967
), `444` = c(5.06134249676025, 14.5442494311861, -0.399445049232868,
7.45775961504073, 9.92629675808998)), row.names = c("hsa_let_7a_3p",
"hsa_let_7a_5p", "hsa_let_7b_3p", "hsa_let_7b_5p", "hsa_let_7c_5p"
), class = "data.frame")
df.miRNA.cpm$miRNA <- rownames(df.miRNA.cpm)
ss.survival.shiny.miRNA.miRNA <- structure(list(ID = c("86", "175", "217", "394", "444"), TimeDiff = c(71.0416666666667,
601.958333333333, 1130, 1393, 117.041666666667), Status = c(1L,
1L, 0L, 0L, 1L)), row.names = c(NA, 5L), class = "data.frame")
Joint the two example data frames:
data_prep.miRNA <- df.miRNA.cpm %>%
tidyr::pivot_longer(-miRNA, names_to = "ID") %>%
left_join(ss.survival.shiny.miRNA.miRNA)
Example of the joined data:
> data_prep.miRNA
# A tibble: 153,033 x 5
miRNA ID value TimeDiff Status
<chr> <chr> <dbl> <dbl> <int>
1 hsa_let_7a_3p 86 5.58 71.0 1
2 hsa_let_7a_3p 175 5.22 602. 1
3 hsa_let_7a_3p 217 5.43 1130 0
4 hsa_let_7a_3p 394 -1.14 1393 0
5 hsa_let_7a_3p 444 5.06 117. 1
6 hsa_let_7a_3p 618 4.37 1508 0
7 hsa_let_7a_3p 640 2.46 1409 0
8 hsa_let_7a_3p 829 0.435 919. 0
9 hsa_let_7a_3p 851 -1.36 976. 0
10 hsa_let_7a_3p 998 3.87 1196. 0
# … with 153,023 more rows
For a selected MicroRNA this works:
fitSurv <- survfit(Surv(data$TimeDiff, data$Status) ~ paste(cut(value , quantile(value , probs = c(0, 0.8)), include.lowest=T)), data = data_prep.miRNA[grep("hsa_let_7a_3p",data_prep.miRNA$miRNA),])
Shiny:
ui.miRNA <- fluidPage(
selectInput("MicroRNA", "miRNA", choices = unique(data_prep.miRNA$miRNA)),
plotOutput("myplot"))
server <- function(input, output, session) {
data_selected <- reactive({
filter(data_prep.miRNA, miRNA %in% input$MicroRNA)
})
output$myplot <- renderPlot({
fitSurv <- survfit(Surv("TimeDiff", "Status") ~ paste(cut("value" , quantile("value" , probs = c(0, 0.8)), include.lowest=T)), data = data_selected)
ggsurvplot(fitSurv ,title="", xlab="Time (Yrs)", ylab="Survival prbability",
font.main = 8,
font.x = 8,
font.y = 8,
font.tickslab = 8,
font.legend=8,
pval.size = 3,
pval.coord = c(1000,1),
size=0.4,
legend = "right",
censor.size=2,
break.time.by = 365,
pval =T,#"p=0.003",#"p=0.41",
#xscale=365,
#palette = c("#E7B800", "#2E9FDF"),
#ggtheme = theme_bw(),
risk.table = F,
xscale=365.25,
xlim=c(0,7*365))
})
}
shinyApp(ui.miRNA, server)

Answer 1

There are several mistakes in this statement:
fitSurv <-
survfit(Surv("TimeDiff", "Status") ~ paste(cut("value", quantile("value", probs = c(0, 0.8)), include.lowest=T)),
data = data_selected)
First, data_selected is a reactive conductor, not a dataframe. If you want the dataframe returned by this reactive conductor, you have to use parentheses: data_selected().
Next, you must not quote the variables: TimeDiff and not "TimeDiff", etc.
The paste command is useless.
Your cut produces only one category and the NA category. To get two intervals as categories, use probs = c(0, 0.8, 1) in quantile.
Finally it is not a good idea to use T for TRUE, because T can be set to any R object, while TRUE is a reserved work.
To conclude, here is the corrected code:
fitSurv <-
survfit(Surv(TimeDiff, Status) ~ cut(value, quantile(value, probs = c(0, 0.8, 1)), include.lowest=TRUE),
data = data_selected())