ANOCVA in R: A Software to Compare Clusters between Groups and Its Application to the Study of Autism Spectrum Disorder.
Understanding how brain activities cluster can help in the diagnosis of neuropsychological disorders. Thus, it is important to be able to identify alterations in the clustering structure of functional brain networks. Here, we provide an R implementation of Analysis of Cluster Variability (ANOCVA), which statistically tests (1) whether a set of brain regions of interest (ROI) are equally clustered between two or more populations and (2) whether the contribution of each ROI to the differences in clustering is significant. To illustrate the usefulness of our method and software, we apply the R package in a large functional magnetic resonance imaging (fMRI) dataset composed of 896 individuals (529 controls and 285 diagnosed with ASD-autism spectrum disorder) collected by the ABIDE (The Autism Brain Imaging Data Exchange) Consortium. Our analysis show that the clustering structure of controls and ASD subjects are different (p< 0.001) and that specific brain regions distributed in the frontotemporal, sensorimotor, visual, cerebellar, and brainstem systems significantly contributed (p< 0.05) to this differential clustering. These findings suggest an atypical organization of domain-specific function brain modules in ASD.
Department of Computer Science, Institute of Mathematics and Statistics, University of São Paulo São Paulo, Brazil.
Maciel C
MC
Vidal
Center of Mathematics, Computation, and Cognition, Universidade Federal do ABC Santo André, Brazil.
João R
JR
Sato
Hospital Israelita Albert Einstein São Paulo, Brazil.
Joana B
JB
Balardin
Deparment of Psychology and Princeton Neuroscience Institute, Princeton University Princeton, NJ, USA.
Daniel Y
DY
Takahashi
Department of Computer Science, Institute of Mathematics and Statistics, University of São Paulo São Paulo, Brazil.
André
A
Fujita
ABIDE; Analysis of Cluster Variability; fMRI; functional brain network; silhouette statistic