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skeletal running and installation instruction
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tashrifbillah committed Apr 22, 2020
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![](pnl-bwh-hms.png)

Outlier detection tool utilizing FreeSurfer segmentation statistics, built using https://plotly.com/dash/


Outlier detection tool utilizing FreeSurfer segmentation statistics, built using https://plotly.com/dash .
However, it can be used for any table that has properties on the first row and subject ids on the first column.
Potential applications include [TBSS](https://github.com/pnlbwh/TBSS/blob/master/docs/TUTORIAL.md#step-6-roivoxelwise-analysis) roi statistics, and group-level statistics generated by [mriqc](https://github.com/poldracklab/mriqc).

# Installation

Clone the repository:

git clone https://github.com/pnlbwh/freesurfer-analysis.git

On Python 3, installation of dependencies can be as simple as:

pip install -r requirements.txt

# Running

* Visualize summary on web browser (http://localhost:8050/):

```bash
# comma separted (default)
python scripts\generate-summary.py -i path\to\asegstats_lh.csv -o \tmp\fs-stats\
# tab separated
python scripts\generate-summary.py -i path\to\asegstats_lh.csv -t tab -o \tmp\fs-stats\
```

* Enable roi rendering (for FreeSurfer only) with visualization:


python scripts\generate-summary.py -i path\to\asegstats_lh.csv -o \tmp\fs-stats\ -t path\to\sub-$\anat\freesurfer


* Generate input table from FreeSurfer statistics:


python scripts\stats2table.py -c path\to\caselist.txt -t path\to\sub-$\anat\freesurfer -o \tmp\fs-stats



# Troubleshooting
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