RobertJirsaraie/meg-mri-surrogate-biomarkers-aging-2020

library and scripts for data analysis and visualization for Engemann at et al. 2020

paper-brain-age-figures

Figure repo for Engemann et al 2020 brain age paper.

Dependencies

Making the figures requires a:

1. the (non-committed) ./data directory (obtained from the authors)
2. a recent Python install including (>=3.5), ideally Anaconda, with Pandas. For details, see file: 'python_requirements.txt'
3. ideally, a recent R Version (>= 3.0).

R dependencies

I did my best to keep the R dependencies flat, avoiding the tidyverse and other meta-packages. All logic and control flow is written in conservative base R and avoids pipe operators and other high-level syntax. The following visualization packages are needed to run the code in a pure R console:

• ggplot2
• ggbeeswarm
• ggrepel

To build the Markdown and HTML, you will also need:

• rmarkdown
• knitr

The dependencies themselves have rather flat dependencies. Ggplot, may depend on a few elements of the tidyverse. However, running the code here should be possible with a rather minimalistic R setup.

Running the code

The figure elements are created through R scripts, which at the same time implement elements of literate programming through RMarkdown directives.

The prinicipal R scripts begin follow the figure_*.r pattern and can be run in the R console or can be compiled through Rmarkdown into HTML outputs. In both cases, the figure elements are created and written to ./figures.

To build the figures together with the HTML, please consider the Makefile. You can build a single figure:

make fig2

Or all figures:

make all