TY - GEN
T1 - Integration of SNPs-FMRI-methylation data with sparse multi-CCA for schizophrenia study
AU - Hu, Wenxing
AU - Lin, Dongdong
AU - Calhoun, Vince D.
AU - Wang, Yu Ping
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/10/13
Y1 - 2016/10/13
N2 - Schizophrenia (SZ) is a complex mental disorder associated with genetic variations, brain development and activities, and environmental factors. There is an increasing interest in combining genetic, epigenetic and neuroimaging datasets to explore different level of biomarkers for the correlation and interaction between these diverse factors. Sparse Multi-Canonical Correlation Analysis (sMCCA) is a powerful tool that can analyze the correlation of three or more datasets. In this paper, we propose the sMCCA model for imaging genomics study. We show the advantage of sMCCA over sparse CCA (sCCA) through the simulation testing, and further apply it to the analysis of real data (SNPs, fMRI and methylation) from schizophrenia study. Some new genes and brain regions related to SZ disease are discovered by sMCCA and the relationships among these biomarkers are further discussed.
AB - Schizophrenia (SZ) is a complex mental disorder associated with genetic variations, brain development and activities, and environmental factors. There is an increasing interest in combining genetic, epigenetic and neuroimaging datasets to explore different level of biomarkers for the correlation and interaction between these diverse factors. Sparse Multi-Canonical Correlation Analysis (sMCCA) is a powerful tool that can analyze the correlation of three or more datasets. In this paper, we propose the sMCCA model for imaging genomics study. We show the advantage of sMCCA over sparse CCA (sCCA) through the simulation testing, and further apply it to the analysis of real data (SNPs, fMRI and methylation) from schizophrenia study. Some new genes and brain regions related to SZ disease are discovered by sMCCA and the relationships among these biomarkers are further discussed.
UR - http://www.scopus.com/inward/record.url?scp=85009126505&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85009126505&partnerID=8YFLogxK
U2 - 10.1109/EMBC.2016.7591436
DO - 10.1109/EMBC.2016.7591436
M3 - Conference contribution
C2 - 28269013
AN - SCOPUS:85009126505
T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
SP - 3310
EP - 3313
BT - 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016
Y2 - 16 August 2016 through 20 August 2016
ER -