Published August 3, 2018
| Version v1.2.0
Software
Open
FCP-INDI/C-PAC: CPAC Version 1.2.0 Beta
Authors/Creators
- Steve Giavasis1
- Daniel Clark2
- Ranjit
- Sharad Sikka3
- nrajamani3
- Zarrar Shehzad4
- John Pellman5
- Caroline Froehlich
- Ranjit Khanuja
- Brian Cheung6
- Cameron Craddock7
- Anibal Sólon1
- Floris van Vugt
- Sebastian Urchs
- James Kent8
- Ilkay Isik9
- Daniel Lurie10
- Yaroslav Halchenko11
- Adam Liska12
- Rosalia Tungaraza
- joshua vogelstein13
- Asier Erramuzpe
- Aimi Watanabe
- Dan Kessler14
- Chris Filo Gorgolewski15
- 1. Child Mind Institute
- 2. @LiveRamp
- 3. CYAN INC
- 4. Yale University
- 5. Columbia University Libraries @cul
- 6. UC Berkeley
- 7. Dell Medical School, University of Texas, Austin
- 8. @HBClab
- 9. Max Planck Institute for Empirical Aesthetic
- 10. University of California, Berkeley
- 11. Dartmouth College, @Debian, @DataLad, @PyMVPA, @fail2ban
- 12. University of Trento
- 13. johns hopkins university
- 14. University of Michigan
- 15. Stanford University
Description
Dear Colleagues,
We are happy to inform you that we have released CPAC Version 1.2.0 Beta.
New Features
- Multivariate Distance Matrix Regression (MDMR). Exploratory, connectome-wide group-level analysis that allows researchers to explore relationships between patterns of functional connectivity and phenotypic variables. Compared to traditional univariate techniques which require rigorous correction for multiple comparisons, this multivariate approach significantly reduces the number of connectivity-phenotype comparisons needed for connectome-wide associations studies. (https://www.ncbi.nlm.nih.gov/pubmed/24583255)
Improvements
- Improved Command-Line Interface. C-PAC is now much easier to use through the command-line interface using the "cpac" CLI tool. Users can kick off individual and group-level analyses using a nested menu, generate new pipeline and data configuration files, and set up FSL FEAT model presets, all without using the Graphical User Interface.
- Increased Skull-Stripping Configurability. You can now modify the full range of parameters for both AFNI's 3dSkullStrip and FSL's BET for anatomical skull-stripping during preprocessing.
- Group-level Analysis Usability. Group-level analyses now also accept tab-separated (.tsv) files for phenotypic information. This allows users to seamlessly pull in the participants.tsv files which often accompany BIDS datasets.
- Default pipeline configuration. For those who don't want the options, C-PAC can run as a turnkey system using parameter selections recommended by our team
Error Fixes
- An error in v1.1.0 that was causing the QC pages to crash on SNR image generation in some pipeline runs has been fixed.
Coming Soon (Release 1.3 early Fall)
- Bootstrap Analysis for Stable Clusters (BASC)
- Inter-subject Correlation (ISC)
- Independent Components Analysis (ICA)-based Denoising
- More FSL Group-Level Analysis presets
- Supervised learning
Updated user documentation for this release can be found here: http://fcp-indi.github.io/
And as always, you can contact us here for user support and discussion: https://groups.google.com/forum/#!forum/cpax_forum
Files
FCP-INDI/C-PAC-v1.2.0.zip
Files
(28.2 MB)
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Additional details
Related works
- Is supplement to
- https://github.com/FCP-INDI/C-PAC/tree/v1.2.0 (URL)