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Ever wondered how to analyse your growth curves, either coming from IVIS, caliper or other biological measurements? Look no more, this package provides a suite of functions and tutorials that help you in performing the crucial step of statistical analysis from your longitudinal data.

Installation

If you don’t have devtools installed yet, install it first and then install the package.

# install.packages("devtools")
devtools::install_gitlab("upbri/biogrowleR")

Usage

There are several use cases for the package, you might want to just explore the data first or want to perform statistical analysis. To explore the data, check the two functions shown below for an idea. For the statistical analysis check the article Analysis workflow for IVIS data on the website

https://upbri.gitlab.io/biogrowleR

library(biogrowleR)

Visualizing each individual measurement over time

It is very important to check the individual growth curves, the function below provides this option.

plot_outcome_by_id(
    t110_ivis_long,
    x = "days_after_treatment",
    y = "log10tf",
    color = "treatment",
    wrap_on = "id"
)

## Warning: Removed 2 rows containing non-finite values (stat_smooth).

## Warning: Removed 2 rows containing missing values (geom_point).

Summary of data

A glimpse of the data in a single plot with a summary is usually useful, the function below provides this option.

plots <- biogrowleR::plot_summary_growth_curves(t110_ivis_long)

cowplot::plot_grid(
    plotlist = plots,
    ncol = 1
)

Tutorials

For more details on how these functions are used in the context of a statistical analysis, check it out our tutorials on how to analyse the growth curves. You can find them at:

https://upbri.gitlab.io/biogrowleR/articles/

Remember, these tutorials are living documents and should be considered as basis for an analysis. You might have to deviate from what is there depending on your data.

Contributing to the package

This is a resource for the community, so if you have a suggestion, question or issues, please open an issue here on gitlab. Also we are very happy to hear suggestions or even alternative analysis for the tutorials.