README.Rmd

---
title: "Introduction to Neuroimaging Data Visualisaion in R"
output: github_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```



These notebooks were developed to be presented at the TrainTrack 2021 edition of the [OHBM BrainHack](https://ohbm.github.io/hackathon2021/).

This short series of R-notebooks will introduce to to some of the neuroimaging data visualization tools  R. You can work though these notebooks on RStudio Cloud, or locally on Rstudio. If you are using Rstudio cloud, or have github installed, clone this get repo by typing the following in to the terminal: 

`git clone https://github.com/sidchop/neuRo-vis-BrainHack-2021.git`


## Structure 
        
We will go though how to visualize 4 different types of data: 

* [Voxel-level data](https://github.com/sidchop/neuRo-vis-BrainHack-2021/blob/main/voxel.Rmd) \

* [ROI-level data](https://github.com/sidchop/neuRo-vis-BrainHack-2021/blob/main/roi.Rmd) \

* [Edge-level data](https://github.com/sidchop/neuRo-vis-BrainHack-2021/blob/main/edge.Rmd)  \

* [Vertex-level data](https://github.com/sidchop/neuRo-vis-BrainHack-2021/blob/main/vertex.Rmd) *(Note: This note book will not work properly on RStudio Cloud due to space and RAM requirements. Also, visualisation will open in a new window (RGL graphics device), not within Rstudio)* \
 

## Pre-requisites

You will need a basic understanding of R syntax. A understanding of R-Markdown syntax will be helpful, but not essential. 


## Questions?
If you run into any problems while executing these notebooks of have any questions,
please open an [issue](https://github.com/sidchop/neuRo-vis-BrainHack-2021/issues) and describing the problem or question. You can also email me at sid.chopra@monash.edu. 

If you are interested in plotting gifti and cifti data, check out:

* [ciftiTools](https://github.com/mandymejia/ciftiTools)
* [Blog by Jo Etzel on plotting gifti data](https://mvpa.blogspot.com/2020/03/volume-and-surface-brain-plotting-knitr.html)


## Acknowledgements
 * Voxel-level data: Thanks to [John Muschelli](https://github.com/muschellij2) for developing `neurobase` and providing great documentation. 
 * ROI-level data: Thanks to [Athanasia Mowinckel](https://github.com/Athanasiamo) for developing `ggseg` & `ggseg3D`, and her wonderful blog posts on how to use these packages. 
 * Vertex-level data: Thanks to [Tim Schäfer & Christine Ecker](https://github.com/dfsp-spirit/fsbrain) for developing fsbrain, a timely and much needed package.