Structured sparse canonical correlation analysis for brain imaging genetics: an improved GraphNet method

Bioinformatics
Lei DuAlzheimer’s Disease Neuroimaging Initiative

Abstract

Structured sparse canonical correlation analysis (SCCA) models have been used to identify imaging genetic associations. These models either use group lasso or graph-guided fused lasso to conduct feature selection and feature grouping simultaneously. The group lasso based methods require prior knowledge to define the groups, which limits the capability when prior knowledge is incomplete or unavailable. The graph-guided methods overcome this drawback by using the sample correlation to define the constraint. However, they are sensitive to the sign of the sample correlation, which could introduce undesirable bias if the sign is wrongly estimated. We introduce a novel SCCA model with a new penalty, and develop an efficient optimization algorithm. Our method has a strong upper bound for the grouping effect for both positively and negatively correlated features. We show that our method performs better than or equally to three competing SCCA models on both synthetic and real data. In particular, our method identifies stronger canonical correlations and better canonical loading patterns, showing its promise for revealing interesting imaging genetic associations. The Matlab code and sample data are freely available at http://www.iu.edu/∼...Continue Reading

References

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Dec 5, 2015·Brain Informatics and Health : 8th International Conference, BIH 2015, London, UK, August 30-September 2, 2015. Proceedings·Lei DuLi Shen

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Citations

Feb 14, 2017·Genetic Epidemiology·Junghi KimUNKNOWN Alzheimer's Disease Neuroimaging Initiative
Mar 23, 2017·IEEE Transactions on Medical Imaging·Ali-Reza Mohammadi-NejadHamid Soltanian-Zadeh
Oct 3, 2017·Bioinformatics·Lei DuUNKNOWN Alzheimer’s Disease Neuroimaging Initiative
Mar 10, 2018·Human Molecular Genetics·Chun Chieh FanAnders M Dale
Jul 12, 2018·IEEE Transactions on Medical Imaging·Alexej GossmannYu-Ping Wang
Mar 16, 2017·Scientific Reports·Xiaoke HaoUNKNOWN Alzheimer’s Disease Neuroimaging Initiative
Jun 28, 2020·Human Brain Mapping·Xiaowei ZhuangDietmar Cordes
Oct 27, 2017·Scientific Reports·Lei DuUNKNOWN Alzheimer’s Disease Neuroimaging Initiative
Nov 6, 2018·Brain Informatics·Sjoerd M H HuismanUNKNOWN Alzheimer’s Disease Neuroimaging Initiative
Mar 19, 2021·Medical Image Analysis·Lei DuThe Alzheimer's Disease Neuroimaging Initiative
Apr 3, 2021·Nature Computational Science·Brian B AvantsJames R Stone
Aug 14, 2021·Circulation. Cardiovascular Imaging·Matthew NayorRamachandran S Vasan
Aug 28, 2020·Computer Methods and Programs in Biomedicine·Mansu KimJin Whan Cho

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Brain Informatics and Health : 8th International Conference, BIH 2015, London, UK, August 30-September 2, 2015. Proceedings
Lei DuLi Shen
Medical Image Computing and Computer-assisted Intervention : MICCAI
Lei DuAlzheimer's Disease Neuroimaging Initiative
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