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# Tutorial : Workflows

This section presents several tutorials on how to setup and use pipelines. Make sure that you have the requirements satisfied and go through the steps required for the analysis tutorials.

## Essential reading

- Pipeline 101
- Pipeline 102
- Pipeline 103
- MapNode, iterfield, and iterables explained
- DataGrabber and DataSink explained

## Beginner’s guide

By Michael Notter. Available here

## Example workflows

- dMRI: Camino, DTI
- dMRI: Connectivity - Camino, CMTK, FreeSurfer
- dMRI: Connectivity - MRtrix, CMTK, FreeSurfer
- dMRI: DTI - Diffusion Toolkit, FSL
- dMRI: HARDI - Diffusion Toolkit, FSL
- dMRI [DTI, FSL]
- dMRI: Group connectivity - Camino, FSL, FreeSurfer
- dMRI: Group connectivity - MRtrix, FSL, FreeSurfer
- dMRI: DTI - MRtrix, FSL
- dMRI: TBSS on NKI RS data
- fMRI: surface smooth - FreeSurfer, SPM
- fMRI: FSL
- fMRI: FEEDS - FSL
- fMRI: FSL reuse workflows
- fMRI: NiPy GLM, SPM
- fMRI: OpenfMRI.org data, FSL
- fMRI: Coregistration - Slicer, BRAINS
- fMRI: SPM, FSL
- fMRI: SPM Auditory dataset
- fMRI: DARTEL, SPM
- fMRI: Famous vs non-famous faces, SPM
- fMRI: SPM nested workflows
- HOWTO: Using caching without using Workflow
- rsfMRI: FSL - CSF regressed
- rsfMRI: FSL, Nipype, tCompCorr
- Paper: Smoothing comparison
- sMRI: Using new ANTS for creating a T1 template
- sMRI: Using ANTS for registration
- sMRI: Using new ANTS for creating a T1 template (ITK4)
- sMRI: FreeSurfer
- sMRI: Regional Tessellation and Surface Smoothing
- Workflow from scratch
- Workshop: Dartmouth College 2010

## Requirements

> All tutorials

> - Release 0.4 of nipype and it’s dependencies have been installed

> Analysis tutorials

> - FSL, FreeSurfer, Camino, ConnectomeViewer and MATLAB are available and callable from the command line
> - SPM 5/8 is installed and callable in matlab
> - Space: 3-10 GB

## Checklist for analysis tutorials

For the analysis tutorials, we will be using a slightly modified version of the FBIRN Phase I travelling data set.

### Step 0

Download and extract the Pipeline tutorial data (429MB).

(checksum: 56ed4b7e0aac5627d1724e9c10cd26a7)

### Step 1.

Ensure that all programs are available by calling `bet`, `matlab` and then `which spm` within matlab to ensure you have spm5/8 in your matlab path.

### Step 2.

You can now run the tutorial by typing `python tutorial_script.py` within the nipype-tutorial directory. This will run a full first level analysis on two subjects following by a 1-sample t-test on their first level results. The next section goes through each section of the tutorial script and describes what it is doing.