Repository for the NIMH Workshop on Open and Reproducible Neuroscience on Aug 1 & 2, 2017.
Many thanks to everyone who helped make this workshop possible and to everyone who attended.
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| Satra Ghosh | Yarik Halchenko | Wolfgang Resch | Afif Elghraoui | Adam Thomas | John Lee | Dylan Nielson |
| MIT | Dartmouth | NIH HPC Team | NIH HPC Team | NIMH DSST | NIMH DSST | NIMH DSST |
Persistent location for the singularity image used in this workshop: "/data/classes/RepNeurSci/images/nih-workshop-2017-latest.img" on NIH hpc systems. Alternatively, you can build the image yourself by following the instructions at the end of the course scratchpad
Adam opened the course with a presentation on the reasons for doing open, reproducible science.
John led the setup of our working environment for the course.
Wolfgang and Afif led an interactive session on singularity containers: Slides, Demo Readme.
John presented a Git refresher.
Yarik told everyone about DataLad and walked us through a demo of using DataLad to manage datasets with git-annex.
Closing out the Tuesday, Dylan walked everyone through the first half of Nipype's Python Tutorial.
Dylan took everyone through Nipype's Python Tutorial up to the final Module's section.
Satra presnted an introduction to Nipype and hands-on reproducible analytics with a walkthough of the preprocessing tutorial
Satra gave us a live demo of using Heudiconv to convert dicoms into a BIDS dataset.
Workshop scratch pad
Workshop setup instructions. For a newer version of this see here.
Ask questions on NeuroStars
Join the Brainhack community on Slack or look through the archives
Learn Git game
Learn Python with Code Academy
NeuroDocker
DataLad
NIMH DSST's Heudiconv scripts(link coming soon)
Nipype Github
Nipype Tutorials
Nipype Documentation
Nipype Apps
Mindboggle
Configurable Pipeline for the Analysis of Connectomes
FMRI Prep
MRIQC
heudiconv example