ArticleJournal of the American Statistical Association2014
Bayesian Generalized Low Rank Regression Models for Neuroimaging Phenotypes and Genetic Markers.
Article in Journal of the American Statistical Association, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.
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Who cites it
35 citing papers in PubMed.
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- High-Dimensional Multiresponse Partially Functional Linear Regression.Statistics in medicine · 2025Article
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- Safety signal detection with control of latent factors.Statistics in medicine · 2024Article
- Neuroimaging feature extraction using a neural network classifier for imaging genetics.BMC bioinformatics · 2023Article
- Bayesian nonparametric method for genetic dissection of brain activation region.Frontiers in neuroscience · 2023Article
- Orthogonalized Kernel Debiased Machine Learning for Multimodal Data Analysis.Journal of the American Statistical Association · 2023Article
- Decoding Genetic Markers of Multiple Phenotypic Layers Through Biologically Constrained Genome-To-Phenome Bayesian Sparse Regression.Frontiers in molecular medicine · 2022Article
- Multivariate Analysis and Modelling of multiple Brain endOphenotypes: Let's MAMBO!Computational and structural biotechnology journal · 2021Review
- L2RM: Low-rank Linear Regression Models for High-dimensional Matrix Responses.Journal of the American Statistical Association · 2020Article
- Brain Imaging Genomics: Integrated Analysis and Machine Learning.Proceedings of the IEEE. Institute of Electrical and Electronics Engineers · 2020Article
- SOFAR: Large-Scale Association Network Learning.IEEE transactions on information theory · 2019Article
- Structured Genome-Wide Association Studies with Bayesian Hierarchical Variable Selection.Genetics · 2019Article
- A Review of Statistical Methods in Imaging Genetics.The Canadian journal of statistics = Revue canadienne de statistique · 2019Article
- Spatial correlations exploitation based on nonlocal voxel-wise GWAS for biomarker detection of AD.NeuroImage. Clinical · 2019Article
- Robust and Discriminative Brain Genome Association Study.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention · 2019Article
- Groupwise envelope models for imaging genetic analysis.Biometrics · 2017Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
We propose a Bayesian generalized low rank regression model (GLRR) for the analysis of both high-dimensional responses and covariates. This development is motivated by performing searches for associations between genetic variants and brain imaging phenotypes. GLRR integrates a low rank matrix to approximate the high-dimensional regression coefficient matrix of GLRR and a dynamic factor model to model the high-dimensional covariance matrix of brain imaging phenotypes. Local hypothesis testing is developed to identify significant covariates on high-dimensional responses. Posterior computation proceeds via an efficient Markov chain Monte Carlo algorithm. A simulation study is performed to evaluate the finite sample performance of GLRR and its comparison with several competing approaches. We apply GLRR to investigate the impact of 1,071 SNPs on top 40 genes reported by AlzGene database on the volumes of 93 regions of interest (ROI) obtained from Alzheimer's Disease Neuroimaging Initiative (ADNI).
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25349462PMC4208701What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.