System Maintenance:
There may be intermittent impact on performance while updates are in progress. We apologize for the inconvenience.
By Topic

Discovering associations in high dimensional imaging-genetics data: A comparison study of dimension reduction and regularisation strategies combined with partial least squares

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

7 Author(s)
Le Floch, E. ; CEA, Neurospin, Gif-sur-Yvette, France ; Pinel, P. ; Tenenhaus, A. ; Trinchera, L.
more authors

Brain imaging is increasingly recognised as an intermediate pheno-type in the understanding of the complex path between genetics and behavioural or clinical phenotypes. In this context, a first goal is to propose methods to identify the part of genetic variability that explains some neuroimaging variability. Here, we investigate multi-variate methods, Partial Least Squares (PLS) regression and Canonical Correlation Analysis (CCA), in order to identify a set of Single Nucleotide Polymorphisms (SNPs) covarying with a set of neuroimaging phenotypes derived from functional Magnetic Resonance Imaging (fMRI). Because in such high-dimensional settings multi-variate methods overfit the data, we propose a comparison study of several dimension reduction and regularisation strategies combined with PLS or CCA. We demonstrate that the combination of univariate filtering and sparse PLS outperforms all other strategies and is able to extract a significant link between a set of SNPs and a set of brain regions activated during a reading task.

Published in:

Biomedical Imaging (ISBI), 2012 9th IEEE International Symposium on

Date of Conference:

2-5 May 2012