Merge pull request #8 from elodiegermani/main

Issues #1 and #2

.github/ISSUE_TEMPLATE/pipeline_reproduction.md

@@ -0,0 +1,16 @@
+---
+name: Pipeline reproduction
+about: Reproduction of a pipeline that is not already reproduce or in reproduction. 
+title: 'Pipeline reproduction ID:'
+labels: "\U0001F6A6 status: awaiting triage"
+assignees: ''
+
+---
+
+**Pipeline details**
+- Original pipeline ID:
+- Original pipeline software package:
+- Type of input data: fMRIprep / raw data
+
+**Additional context**
+Add any other context about the problem here.

.gitignore

@@ -14,7 +14,6 @@ dist/
 downloads/
 eggs/
 .eggs/
-lib/
 lib64/
 parts/
 sdist/

CONTRIBUTING.md

@@ -2,6 +2,8 @@
 
 General guidelines can be found [here](https://docs.github.com/en/get-started/quickstart/contributing-to-projects). 
 
+## Reproduce a pipeline ⌨️
+
 ## Find or propose an issue 📋
 
 Issues are very important for this project. If you want to contribute, you can either **comment an existing issue** or **proposing a new issue**. 

README.md

@@ -25,7 +25,7 @@ However, different analytical choices can cause variation in the results (Botvin
 
 **The goal of the NARPS open pipeline project is to create a codebase reproducing the 70 pipelines of the NARPS project (Botvinik-Nezer et al., 2020) and share this as an open resource for the community**. 
 
-To perform the reproduction, we are lucky to be able to use the description provided by each team available here.
+To perform the reproduction, we are lucky to be able to use the description provided by each team available [here](https://github.com/poldrack/narps/blob/1.0.1/ImageAnalyses/metadata_files/analysis_pipelines_for_analysis.xlsx).
 
 ## To start 
 
@@ -43,24 +43,83 @@ Instructions to download data are available [below](#download-data).
 
 ### Install Docker container
 
-*Coming soon*
+To use the notebooks and launch the pipelines, you need to install the [NiPype](https://nipype.readthedocs.io/en/latest/users/install.html) Python package but also the original software package used in the pipeline (SPM, FSL, AFNI...). 
+
+To facilitate this step, we created a Docker container based on [Neurodocker](https://github.com/ReproNim/neurodocker) that contains the necessary Python packages and software packages. To install the Docker image, use the command below: 
+```
+docker pull elodiegermani/open_pipeline:latest
+```
+
+The image should install itself. Once it's done you can check available images on your system:
+```
+docker images
+```
+
+When the installation is finished, you have to build a container using the command below:
+```
+docker run -ti -p 8888:8888 elodiegermani/open_pipeline
+```
+
+On this commandline, you need to add volumes to be able to link with your local files (original dataset and git repository). If you stored the original dataset in `data/original`, just make a volume with the `narps_open_pipelines` directory:
+```
+docker run -ti -p 8888:8888 -v /users/egermani/Documents/narps_open_pipelines:/home/ elodiegermani/open_pipeline
+``` 
+
+If it is in another directory, make a second volume with the path to your dataset:
+```
+docker run -ti -p 8888:8888 -v /Users/egermani/Documents/narps_open_pipelines:/home/ -v /Users/egermani/Documents/data/NARPS/:/data/ elodiegermani/open_pipeline
+```
+
+After that, your container will be launched! 
+
+#### Other command that could be useful: 
+##### START THE CONTAINER 
+```docker start [name_of_the_container]```
+
+##### VERIFY THE CONTAINER IS IN THE LIST 
+```docker ps ```
+
+##### EXECUTE BASH OR ATTACH YOUR CONTAINER 
+```docker exec -ti [name_of_the_container] bash```
+OR
+```docker attach [name_of_the_container]```
+
+#### Useful command inside the container: 
+##### ACTIVATE CONDA ENVIRONMENT
+```source activate neuro```
+
+##### LAUNCH JUPYTER NOTEBOOK
+```jupyter notebook --port=8888 --no-browser --ip=0.0.0.0```
+
+#### If you did not use your container for a while: 
+##### VERIFY IT STILL RUN : 
+```docker ps -l```
+##### IF YOUR DOCKER CONTAINER IS IN THE LIST, RUN : 
+```docker start [name_of_the_container]```
+##### ELSE, RERUN IT WITH : 
+```docker run -ti -p 8888:8888 -v /home/egermani:/home [name_of_the_image]```
+
+#### To use SPM inside the container, use this command at the beginning of your script:
+```
+from nipype.interfaces import spm
+matlab_cmd = '/opt/spm12-r7771/run_spm12.sh /opt/matlabmcr-2010a/v713/ script'
+spm.SPMCommand.set_mlab_paths(matlab_cmd=matlab_cmd, use_mcr=True)
+```
 
 ### Download data 
 
 #### Original dataset
 
-File containing pipeline description is available in `/data/original`.
-
 The dataset used for the `/src/reproduction_*.ipynb` notebooks can be downloaded [**here**](https://openneuro.org/datasets/ds001734/versions/1.0.5).
 
-The data must be stored in a directory inside the `data/original` directory. 
+I recommand to store the data in a directory inside the `data/original` directory. 
 
 I recommand to download it with **Datalad**. If you want to use it, install [**Datalad**](http://handbook.datalad.org/en/latest/intro/installation.html#install), place yourself in the `data/original` directory and run `datalad install ///openneuro/ds001734`.
 After, you can download all the files by running `datalad get ./*` and if you only want parts of the data, replace the * by the paths to the desired files. 
 
 #### Derived data
 
-Derived data such as original stat maps from teams and reproduced stat maps can be downloaded from [NeuroVault](www.neurovault.org) (Gorgolewski & al, 2015). 
+Derived data such as original stat maps from teams and reproduced stat maps can be downloaded from [NeuroVault](https://www.neurovault.org) (Gorgolewski & al, 2015). 
 
 *Coming soon*