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https://github.com/rob-luke/fnirs-apps-demo
Example and automated usage of fNIRS Apps
https://github.com/rob-luke/fnirs-apps-demo
fnirs signal-processing
Last synced: 9 days ago
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Example and automated usage of fNIRS Apps
- Host: GitHub
- URL: https://github.com/rob-luke/fnirs-apps-demo
- Owner: rob-luke
- License: bsd-3-clause
- Created: 2021-07-19T08:37:55.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2022-03-10T00:50:20.000Z (over 2 years ago)
- Last Synced: 2024-10-15T18:30:52.532Z (24 days ago)
- Topics: fnirs, signal-processing
- Homepage: http://fnirs-apps.org
- Size: 84 KB
- Stars: 1
- Watchers: 2
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# fNIRS Apps Example
[*fNIRS Apps*](http://fnirs-apps.org) are standalone neuroimaging pipelines inspired by BIDS Apps.
This repository demonstrates how you can use fNIRS Apps to specify your complete analysis pipleline, from raw data to group level GLM statistical analysis.
This example utilises the boutiques framework.
[*Boutiques*](http://boutiques.github.io) is a descriptive command-line framework automating analysis.
It allows you to specify the app you wish to run and the parameters you wish to use.
Boutiques will validate your parameters before running the app, minimising the risk of error.
All *fNIRS Apps* are registered with boutiques, you can search for fNIRS apps using the `bosh` tool from *boutiques* by running:
```bash
➜ ~ bosh search 'fNIRS Apps'
```
which will return something like...
```bash
[ INFO ] Showing 4 of 4 result(s), exluding 0 deprecated result(s).
ID TITLE DESCRIPTION
zenodo.5112758 fNIRS Apps: Sourcedata to BIDS Create fNIRS BIDS datasets from source d...
zenodo.5112722 fNIRS Apps: Scalp Coupling Index Compute Scalp Coupling Index and mark BI...
zenodo.5112773 fNIRS Apps: Quality Reports Generate quality reports for fNIRS data
zenodo.5113225 fNIRS Apps: GLM Pipeline A GLM pipeline for fNIRS data
```
which includes the app ID (which is automatically updated each time a new version is release),
the app names, and brief description.
We must also provide the parameters to be used with each app.
These are provided in the attached code as json files.
Combining the above information we would run a single app as:
```bash
bosh exec launch zenodo.5112758 01-raw-data-to-bids.json -v /path/to/data:/bids_dataset
```
In this example we run the following apps in turn with:
* Convert raw data in vendor format to a BIDS dataset
`bosh exec launch zenodo.5112758 01-raw-data-to-bids.json -v /path/to/data:/bids_dataset`
* Calculate the scalp coupling index for each channel and mark channels with SCI<0.7 as bad
`bosh exec launch zenodo.5112722 02-compute-sci.json -v /path/to/data/:/bids_dataset`
* Generate a data quality report for each file
`bosh exec launch zenodo.5112773 03-generate-quality-reports.json -v /path/to/data/:/bids_dataset`
* Execute a GLM analysis on the dataset, including a group level mixed effects analysis
`bosh exec launch zenodo.5113225 04-run-glm-analysis.json -v /path/to/data/:/bids_dataset`
This repository uses GitHub actions to automatically run this entire chain of analysis in the could.
It is run each time an app is updated to ensure it does not break.
You can view the analysis and output by clicking on the `Actions` tab at the top of the page.
View the github workflow to see how each bosh command is run in turn.