Fused lasso regression for identifying differential correlations in brain connectome graphs
Document Type
Article
Publication Date
10-1-2018
Abstract
In this paper, we propose a procedure to find differential edges between 2 graphs from high-dimensional data. We estimate 2 matrices of partial correlations and their differences by solving a penalized regression problem. We assume sparsity only on differences between 2 graphs, not graphs themselves. Thus, we impose an ℓ2 penalty on partial correlations and an ℓ1 penalty on their differences in the penalized regression problem. We apply the proposed procedure in finding differential functional connectivity between healthy individuals and Alzheimer's disease patients.
Identifier
85050933016 (Scopus)
Publication Title
Statistical Analysis and Data Mining
External Full Text Location
https://doi.org/10.1002/sam.11382
e-ISSN
19321872
ISSN
19321864
First Page
203
Last Page
226
Issue
5
Volume
11
Grant
R01MH101555
Fund Ref
National Institute of Mental Health
Recommended Citation
Yu, Donghyeon; Lee, Sang Han; Lim, Johan; Xiao, Guanghua; Craddock, Richard Cameron; and Biswal, Bharat B., "Fused lasso regression for identifying differential correlations in brain connectome graphs" (2018). Faculty Publications. 8366.
https://digitalcommons.njit.edu/fac_pubs/8366
