While all the computer facilities and datasets will be provided (NITRIC has kindly provided virtual machines) and there is no need for bringing your own machines. Nonetheless you are welcome to use your own laptops since all the work is going to be done remotely.
Day 1 (Saturday)
9 - 9.15: Introduction to the Workshop
9.15 - 10.15: Python and the IPython notebook
Overview of the basic constructs (syntax, datatypes, conditionals) of Python and to using the IPython notebook.
10.15 - 11.00: Scientific computing in Python
Introduction to numpy, scipy and an overview of other scientific packages available in Python.
11.00 - 12.00: Breakout session I
Solve some scientific computing problems within the IPython notebook. Explore extended capabilities of the notebook (e.g., plotting, calling R, launching a IPython Qt terminal to do enhanced debugging)
12.00 - 1.30: Lunch (Provided)
1.30 - 2: Overview of Nipype
History and introduction to Nipype terminology (Interface, Node, MapNode, Workflow, Caching/Working dir, iterables, iterfield, config options, Plugins).
2.00 - 3.00: Scripting with Nipype
How to use Nipype interfaces, caching mechanisms and create simple workflows. Defining inline and Function node functions. Using a DataGrabber and DataSink. Using the IdentityInterface and iterables. When to use MapNodes.
3.00 - 3.30: Coffee (Provided)
3.30 - 5.30: Breakout session II
Create workflows for preprocessing resting and diffusion data that integrates several packages and quality control steps. Explore how to debug when a script fails (logging, config options). Advanced users can work on creating new Nipype interfaces.
5.30 - 6.00: Q&A session
Day 2 (Sunday)
9.00 - 10.30: Creating connectivity matrices or “connectomes”
Using atlases and templates, resampling on vertices and storing thresholded and unthresholded connection matrices using hdf5. Correlations, distances and diffusivity estimates.
10.30 - 12.00: Graph metrics and network analysis
Calculate graph metrics and compare network properties.
12.00 - 1.30: Lunch (Provided)
1.30 - 5.00: Breakout session III (Coffee at 3)
Analyzing and exploring a multi-subject dataset with Nipype and Python scripts.
5.00 - 6.00: Presentations and Q&A session
During breakout sessions and end of day presentations/feedback, participants are encouraged to come and show what they have been working on.
