Basic plots

Load libraries

Import csv

You should have 4 columns of data that look like this:

condition day dead censored
WT 10 2 0
WT 12 0 1
… … … … 
# This is a fictional dataset that is bundled with the package, and is used
# for the purposes of this tutorial
data(sample_data)
dat <- sample_data

head(dat) # see the first few rows
#>   X condition day dead censored sex
#> 1 1        WT   0    0        0   M
#> 2 2        WT   1    2        1   M
#> 3 3        WT   2    1        0   M
#> 4 4        WT   3    1        0   M
#> 5 5        WT   4    3        0   M
#> 6 6        WT   5    1        0   M

To import your own data, do the following:

  1. Export your Excel table as a csv file (eg: your-csv-file.csv). Note that all your conditions must be in the same sheet.
  2. Create an R project in the same folder as your csv file.
  3. Use the following line of code to import your csv file into R.
dat <- read.csv("your-csv-file.csv")
head(dat) # see the first few rows

What conditions are present?

unique(dat$condition)
#> [1] "WT"    "Drug1" "Drug2"

Survival plot

run_bulksurv() plots a survival curve, and outputs median survival, log-rank test and pairwise log-rank test statistics:

p <- run_bulksurv(dat) # Default: survival curve
#> Joining with `by = join_by(x, condition, day, sex, status)`
#> call: formula = Surv(day, status) ~ condition

Mortality plot

Use type = "mortality" for a mortality curve:

p <- run_bulksurv(dat, 
                  print_stats = FALSE, 
                  type = "mortality")
#> Joining with `by = join_by(x, condition, day, sex, status)`
#> call: formula = Surv(day, status) ~ condition