ENIGMA-DTI pipeline Releases

enigma_dti ENIGMA DTI ROI extraction protocol

kochunov@www.nitrc.org (Peter Kochunov) — Thu, 14 Jan 2016 13:37:00 GMT

This is enigma ROI extraction protocol. The executable files are compiled for linux. The source code can be compiled for MAC as long as you have FSL installed

ENIGMA-DTI diffusivity protocol ENIGMA DTI diffusivity protocol

kochunov@www.nitrc.org (Peter Kochunov) — Thu, 14 Jan 2016 13:31:00 GMT

enigma_dti ENIGMA-DTI FA Original Template

nedz@www.nitrc.org (Neda Jahanshad) — Wed, 11 Nov 2015 20:14:00 GMT

ENIGMA DTI-FA template and skeleton

enigma_dti ENIGMA GitHub

nedz@www.nitrc.org (Neda Jahanshad) — Wed, 11 Nov 2015 20:11:00 GMT

for the latest and greatest easy to use code, check out our GitHub page

enigma_dti ENIGMA-DTI FA protocols 2015.11.11.v1.1

nedz@www.nitrc.org (Neda Jahanshad) — Wed, 11 Nov 2015 20:06:00 GMT

ENIGMA-DTI processing. From preprocessing suggestions, quality control scripts, template download, registrations, and skeletonizations. Find it all in this document!!

enigma_dti Third ENIGMA-DTI publication - a report on collaboration between ENIGMA and HCP

kochunov@www.nitrc.org (Peter Kochunov) — Wed, 14 Oct 2015 15:18:00 GMT

enigma_dti Second ENIGMA-DTI publication: Kochunov, NeuroImage 2014

kochunov@www.nitrc.org (Peter Kochunov) — Wed, 14 Oct 2015 15:16:00 GMT

Multi-site study of additive genetic effects on fractional anisotropy of cerebral white matter: Comparing meta and megaanalytical approaches for data pooling.
Neuroimage. 2014 Jul 15;95:136-50.
Combining datasets across independent studies can boost statistical power by increasing the numbers of observations and can achieve more accurate estimates of effect sizes. This is especially important for genetic studies where a large number of observations are required to obtain sufficient power to detect and replicate genetic effects. There is a need to develop and evaluate methods for joint-analytical analyses of rich datasets collected in imaging genetics studies. The ENIGMA-DTI consortium is developing and evaluating approaches for obtaining pooled estimates of heritability through meta-and mega-genetic analytical approaches, to estimate the general additive genetic contributions to the intersubject variance in fractional anisotropy (FA) measured from diffusion tensor imaging (DTI). We used the ENIGMA-DTI data harmonization protocol for uniform processing of DTI data from multiple sites. We evaluated this protocol in five family-based cohorts providing data from a total of 2248 children and adults (ages: 9-85) collected with various imaging protocols. We used the imaging genetics analysis tool, SOLAR-Eclipse, to combine twin and family data from Dutch, Australian and Mexican-American cohorts into one large "mega-family". We showed that heritability estimates may vary from one cohort to another. We used two meta-analytical (the sample-size and standard-error weighted) approaches and a mega-genetic analysis to calculate heritability estimates across-population. We performed leave-one-out analysis of the joint estimates of heritability, removing a different cohort each time to understand the estimate variability. Overall, meta- and mega-genetic analyses of heritability produced robust estimates of heritability.

enigma_dti First ENIGMA-DTI publication Jahanshad 2014

kochunov@www.nitrc.org (Peter Kochunov) — Wed, 14 Oct 2015 15:11:00 GMT

Multi-site genetic analysis of diffusion images and voxelwise heritability analysis: a pilot project of the ENIGMA-DTI working group.
Neuroimage. 2013 Nov 1;81:455-69.
The ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Consortium was set up to analyze brain measures and genotypes from multiple sites across the world to improve the power to detect genetic variants that influence the brain. Diffusion tensor imaging (DTI) yields quantitative measures sensitive to brain development and degeneration, and some common genetic variants may be associated with white matter integrity or connectivity. DTI measures, such as the fractional anisotropy (FA) of water diffusion, may be useful for identifying genetic variants that influence brain microstructure. However, genome-wide association studies (GWAS) require large populations to obtain sufficient power to detect and replicate significant effects, motivating a multi-site consortium effort. As part of an ENIGMA-DTI working group, we analyzed high-resolution FA images from multiple imaging sites across North America, Australia, and Europe, to address the challenge of harmonizing imaging data collected at multiple sites. Four hundred images of healthy adults aged 18-85 from four sites were used to create a template and corresponding skeletonized FA image as a common reference space. Using twin and pedigree samples of different ethnicities, we used our common template to evaluate the heritability of tract-derived FA measures. We show that our template is reliable for integrating multiple datasets by combining results through meta-analysis and unifying the data through exploratory mega-analyses. Our results may help prioritize regions of the FA map that are consistently influenced by additive genetic factors for future genetic discovery studies.