Numerically Perturbed Structural Connectomes from 100 individuals in the NKI Rockland DatasetThis dataset contains the derived connectomes, discriminability scores, and classification performance for structural connectomes estimated from a subset of the Nathan Kline Institute Rockland Sample dataset, and is associated with an upcoming manuscript entitled: Numerical Instabilities in Analytical Pipelines Compromise the Reliability of Network Neuroscience. The associated code for this project is publicly available at: https://github.com/gkpapers/2020ImpactOfInstability. For any questions, please contact Gregory Kiar (gkiar07@gmail.com) or Tristan Glatard (tristan.glatard@concordia.ca). Below is a table of contents describing the contents of this dataset, which is followed by an excerpt from the manuscript pertaining to the contained data. impactofinstability_connect_dset25x2x2x20_inputs.h5 : Connectomes derived from 25 subjects, 2 sessions, 2 subsamples, and 20 MCA simulations with input perturbations. impactofinstability_connect_dset25x2x2x20_pipeline.h5 : Connectomes derived from 25 subjects, 2 sessions, 2 subsamples, and 20 MCA simulations with pipeline perturbations. impactofinstability_discrim_dset25x2x2x20_both.csv : Discriminability scores for each grouping of the...Access is restricted by the data custodian. The collection's description and structure are public; the data is not available for querying through this network.Numerically Perturbed Structural Connectomes from 100 individuals in the NKI Rockland Dataset is published on Viral AI.