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fmriprep-denoise-benchmark

Benchmark denoising strategies available from fmriprep.

https://github.com/simexp/fmriprep-denoise-benchmark

Science Score: 67.0%

This score indicates how likely this project is to be science-related based on various indicators:

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    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
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    .zenodo.json file
    Found .zenodo.json file
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    DOI references
    Found 11 DOI reference(s) in README
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    Academic publication links
    Links to: biorxiv.org, zenodo.org
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    Academic email domains
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    Institutional organization owner
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    JOSS paper metadata
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    Scientific vocabulary similarity
    Low similarity (11.6%) to scientific vocabulary
Last synced: 6 months ago · JSON representation ·

Repository

Benchmark denoising strategies available from fmriprep.

Basic Info
  • Host: GitHub
  • Owner: SIMEXP
  • License: mit
  • Language: Python
  • Default Branch: main
  • Size: 117 MB
Statistics
  • Stars: 16
  • Watchers: 4
  • Forks: 9
  • Open Issues: 0
  • Releases: 5
Created over 4 years ago · Last pushed about 2 years ago
Metadata Files
Readme Changelog License Citation

README.md

Benchmark denoising strategies on fMRIPrep output

DOI

The project is a continuation of load_confounds. The aim is to evaluate the impact of denoising strategy on functional connectivity data, using output processed by fMRIPrep LTS in a reproducible workflow.

Preprint of the manuscript is now on biorxiv. The reporducible Jupyter Book preprint is on NeuroLibre.

Recommandations for those who thought this project is a software

Bad news, this is not a software but a research project. It's more similar to your regular data science project. In other words, the code in this repository reflects the research done for the manuscript, and is not suitable for production level application.

Some useful part of the code has been extracted and further reviewed within SIMEXP lab for deplyment on generic fmriprep derivatives as docker images.

Quick start

bash git clone --recurse-submodules https://github.com/SIMEXP/fmriprep-denoise-benchmark.git cd fmriprep-denoise-benchmark virtualenv env source env/bin/activate pip install -r binder/requirements.txt pip install . make data make book

Dataset structure

  • binder/ contains files to configure for neurolibre and/or binder hub.

  • content/ is the source of the JupyterBook.

  • data/ is reserved to store data for running analysis. To build the book, one will need all the metrics from the study. The metrics are here: DOI The data will be automatically downloaded to content/notebooks/data. You can by pass this step through accessing the Neurolibre preprint DOI!

  • Custom code is located in fmriprep_denoise/. This project is installable.

  • Preprocessing SLURM scripts, and scripts for creating figure for manuscript are in scripts/.

Owner

  • Name: SIMEXP
  • Login: SIMEXP
  • Kind: organization
  • Email: pierre.bellec@criugm.qc.ca
  • Location: Montreal, Canada

Laboratory for brain simulation and exploration

Citation (CITATION.cff) 

cff-version: "1.2.0"
authors:
- family-names: Wang
  given-names: Hao-Ting
  orcid: "https://orcid.org/0000-0003-4078-2038"
- family-names: Meisler
  given-names: Steven L
  orcid: "https://orcid.org/0000-0002-8888-1572"
- family-names: Sharmarke
  given-names: Hanad
- family-names: Clarke
  given-names: Natasha
- family-names: Paugam
  given-names: François
- family-names: Gensollen
  given-names: Nicolas
  orcid: "https://orcid.org/0000-0001-7199-9753"
- family-names: Markiewicz
  given-names: Christopher J
  orcid: "https://orcid.org/0000-0002-6533-164X"
- family-names: Thirion
  given-names: Bertrand
  orcid: "https://orcid.org/0000-0001-5018-7895"
- family-names: Bellec
  given-names: Pierre
  orcid: "https://orcid.org/0000-0002-9111-0699"
doi: 10.5281
message: To reference this work, please cite our reproducible preprint
  in NeuroLibre.
preferred-citation:
  authors:
  - family-names: Wang
    given-names: Hao-Ting
    orcid: "https://orcid.org/0000-0003-4078-2038"
  - family-names: Meisler
    given-names: Steven L
    orcid: "https://orcid.org/0000-0002-8888-1572"
  - family-names: Sharmarke
    given-names: Hanad
  - family-names: Clarke
    given-names: Natasha
  - family-names: Paugam
    given-names: François
  - family-names: Gensollen
    given-names: Nicolas
    orcid: "https://orcid.org/0000-0001-7199-9753"
  - family-names: Markiewicz
    given-names: Christopher J
    orcid: "https://orcid.org/0000-0002-6533-164X"
  - family-names: Thirion
    given-names: Bertrand
    orcid: "https://orcid.org/0000-0001-5018-7895"
  - family-names: Bellec
    given-names: Pierre
    orcid: "https://orcid.org/0000-0002-9111-0699"
  date-published: 2023-06-19
  doi: 10.55458/neurolibre.00012
  journal: NeuroLibre Reproducible Preprints
  publisher:
    name: NeuroLibre
  title: A reproducible benchmark of resting-state fMRI denoising
    strategies using fMRIPrep and Nilearn
  type: preprint
  url: "https://neurolibre.org/papers/10.55458/neurolibre.00012"
title: A reproducible benchmark of resting-state fMRI denoising
  strategies using fMRIPrep and Nilearn

GitHub Events

Total
  • Watch event: 1
  • Pull request event: 3
  • Fork event: 1
Last Year
  • Watch event: 1
  • Pull request event: 3
  • Fork event: 1

Dependencies

binder/requirements.txt pypi
  • awscli ==1.21.0
  • bctpy ==0.5.2
  • jupyter-book ==0.13.0
  • jupytext ==1.14.1
  • matplotlib ==3.4.2
  • myst-parser ==0.15.2
  • nibabel ==4.0.1
  • nilearn ==0.9.1
  • numpy ==1.21.4
  • pandas ==1.3.5
  • plotly ==5.11.0
  • pybids ==0.14.0
  • repo2data ==2.7.0
  • scikit_learn ==1.0.1
  • scipy ==1.7.3
  • seaborn ==0.11.2
  • statsmodels ==0.12.2
  • templateflow ==0.7.2
setup.py pypi