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This is a minimal template for brainlife.io Apps readme files. Use this as a start for your readme file and please cite the funding sources and articles reported here.

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Abcdspec-compliant Run on Brainlife.io

app-example-documentation

This is a minimal example of brainlife.io App README. Please update and add something like the following content...

  1. What the App does, and how it does it at the basic level.
  2. Briefly explain what 1) means for novice users in a language that 1st year psychology student can understand it.
  3. Briefly description of input / output files.

Authors

Contributors

Funding Acknowledgement

brainlife.io is publicly funded and for the sustainability of the project it is helpful to Acknowledge the use of the platform. We kindly ask that you acknowledge the funding below in your publications and code reusing this code.

NSF-BCS-1734853 NSF-BCS-1636893 NSF-ACI-1916518 NSF-IIS-1912270 NIH-NIBIB-R01EB029272

Citations

We kindly ask that you cite the following articles when publishing papers and code using this code.

  1. Avesani, P., McPherson, B., Hayashi, S. et al. The open diffusion data derivatives, brain data upcycling via integrated publishing of derivatives and reproducible open cloud services. Sci Data 6, 69 (2019). https://doi.org/10.1038/s41597-019-0073-y

MIT Copyright (c) 2022 brainlife.io The University of Texas at Austin

Running the App

On Brainlife.io

You can submit this App online at https://doi.org/10.25663/bl.app.1 via the "Execute" tab.

Running Locally (on your machine)

  1. git clone this repo.
  2. Inside the cloned directory, create config.json with something like the following content with paths to your input files.
{
        "track": "./input/track/track.tck",
	"dwi": "./input/dtiinit/dwi_aligned_trilin_noMEC.nii.gz",
	"bvecs": "./input/dtiinit/dwi_aligned_trilin_noMEC.nii.bvecs",
	"bvals": "./input/dtiinit/dwi_aligned_trilin_noMEC.nii.bvals",
        "life_discretization": 360,
        "num_iterations": 100
}
  1. Launch the App by executing main
./main

Sample Datasets

If you don't have your own input file, you can download sample datasets from Brainlife.io, or you can use Brainlife CLI.

npm install -g brainlife
bl login
mkdir input
bl dataset download 5a0e604116e499548135de87 && mv 5a0e604116e499548135de87 input/track
bl dataset download 5a0dcb1216e499548135dd27 && mv 5a0dcb1216e499548135dd27 input/dtiinit

Output

All output files will be generated under the current working directory (pwd). The main output of this App is a file called output.mat. This file contains following object.

fe = 

    name: 'temp'
    type: 'faseval'
    life: [1x1 struct]
      fg: [1x1 struct]
     roi: [1x1 struct]
    path: [1x1 struct]
     rep: []

output_fg.pdb contains all fasicles with >0 weights withtin fg object (fibers)

Product.json

The secondary output of this app is product.json. This file allows web interfaces, DB and API calls on the results of the processing.

Dependencies

This App only requires singularity to run. If you don't have singularity, you will need to install following dependencies.

MIT Copyright (c) 2022 brainlife.io The University of Texas at Austin

About

This is a minimal template for brainlife.io Apps readme files. Use this as a start for your readme file and please cite the funding sources and articles reported here.

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