The goal of ipolygrowth is to calculate bacterial growth curve parameters using fourth degree polynomial functions. Functions are available for a single biological sample or multiple samples.
The package can be installed from CRAN with:
install.packages("ipolygrowth")or the development version from GitHub with:
# install.packages("devtools")
devtools::install_github("https://github.com/kivanvan/ipolygrowth", upgrade = F, quiet = T)Load the packages first.
library(ipolygrowth)
library(dplyr)The example data comes from the growthrates package.
# example data comes from the growthrates package (available on CRAN)
if (!"growthrates" %in% installed.packages()) {install.packages("growthrates")}
data <- growthrates::bactgrowthAlternatively, download the bactgrowth.txt from
here to the
directory of your script. The data can then be read using the following
code.
data <- read.table("bactgrowth.txt", header = TRUE) %>%
mutate(strain = factor(strain, levels = c("D", "R", "T")))This is a basic example which shows you how to use the single sample function:
# subset data to a single biological sample
df.singlesample <- data %>% dplyr::filter(strain == "D", conc == 0)
# calculate growth curve parameters using ipolygrowth function
out.singlesample <- ipg_singlesample(data = df.singlesample, time.name = "time", y.name = "value")
#> max y time is equal to the largest value of "time"The output is a list, including a table of growth parameter estimates, the polynomial model, a table of beta coefficients, and a table of fitted values. Growth parameters include peak growth rate, peak growth time, doubling time (at the peak growth), lag time, max y, and max y time. View the results by calling each list element like:
out.singlesample$estimates
#> peak growth rate peak growth time doubling time lag time max y
#> 1 0.005474298 3.636922 126.6185 0.1231345 0.1073791
#> max y time
#> 1 30For more instructions and the expected output of vignette, please refer to the vignette on CRAN.