This is the repository containing the data and full analysis code used for our publication:
Matheson GJ, Plavén-Sigray P, Forsberg A, Varrone A, Farde L, Cervenka S. Assessment of simplified ratio-based approaches for quantification of PET [11C]PBR28 data. EJNMMI research. 2017 Dec 1;7(1):58.
The analysis begins after time activity curves have been extracted from the dynamic PET images, as this is a reanalysis of a data set which was previously published on. The data is supplied in the RawData folder, and the analysis notebook is provided in the R folder.
Software Requirements
Programs
The analysis is performed using R. For those who have not used R before, you should start by downloading R, and then RStudio. If you wish to compile the report as a pdf, you will also need MiKTeX.
Packages
You will then need several packages for the analysis: these can be installed in R from CRAN: an archive of R packages. This can be performed using the following syntax:
install.packages("packagename")
Packages are loaded using the following syntax:
library(packagename)
You should download the packages which are loaded at the start of the analysis before running the analysis.
Several packages and/or versions of packages used in the analysis are not available from CRAN and are instead hosted on GitHub. These can be installed directly using the devtools package using the following syntax:
library(devtools)
install_github("username/packagename")
Downloading Everything
The best way to download everything is first to download Git if you don't already have it, and then to clone the repository using the terminal (or Git Bash on Windows):
git clone https://github.com/mathesong/PBR28_RatioMethods.git
At this point, you will have downloaded the repository to your computer. If you have not used Git before, I recommend that you follow this short tutorial to get you started.
Reproducing the Analysis
Viewing the Code and Figures
To simply view the code and figures, just click on the R folder within GitHub. I have rendered everything in markdown as the README file, so you can view everything without even cloning the repository.
Running the Code
You should run all code from the R folder. You can set your R environment working directory there using the File Explorer in RStudio, and then clicking More > Set as Working Directory.
Running code blocks step-by-step
Open R/Modelling_and_Analysis.Rmd in RStudio, and click the play buttons in the top right of each code block to step through the code.
Rendering the analysis report documents
Either click on Knit and select the desired output format in RStudio with R/Modelling_and_Analysis.Rmd. Otherwise, run the R/renderFiles.R script.
Questions, Issues, Suggestions, etc
Please either contact me at granville.matheson[at]ki.se, or create an issue on GitHub.