Quantitative trait loci identification for brain endophenotypes via new additive model with random networks
Abstract
The identification of quantitative trait loci (QTL) is critical to the study of causal relationships between genetic variations and disease abnormalities. We focus on identifying the QTLs associated to the brain endophenotypes in imaging genomics study for Alzheimer’s Disease (AD). Existing research works mainly depict the association between single nucleotide polymorphisms (SNPs) and the brain endophenotypes via the linear methods, which may introduce high bias due to the simplicity of the models. Since the influence of QTLs on brain endophenotypes is quite complex, it is desired to design the appropriate non-linear models to investigate the associations of genotypes and endophenotypes.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Sep 01, 2018
- Source ID
- 10.1093/bioinformatics/bty557
Entities
People
- Andrew J. Saykin
- For The Adni
- Heng Huang
- Hong Chen
- Jingwen Yan
- Kwangsik Nho
- Michael Weiner
- Shannon L. Risacher
- Shen Li
- Xiaoqian Wang
Organizations
- Alzheimer's Disease Neuroimaging Initiative
- Indiana University
- National Institutes of Health
- National Natural Science Foundation of China
- National Science Foundation
- University of Pennsylvania
- University of Pittsburgh