ArticleThe Canadian journal of statistics = Revue canadienne de statistique2019
A Review of Statistical Methods in Imaging Genetics.
Article in The Canadian journal of statistics = Revue canadienne de statistique, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
25 citing papers in PubMed, 40 citations in OpenAlex.
- S-GMAS: Genome-Wide Mediation Analysis With Brain Subcortical Shape Mediators.Human brain mapping · 2025Article
- STATISTICAL INFERENCE FOR MEAN FUNCTIONS OF COMPLEX 3D OBJECTS.Statistica Sinica · 2025Article
- Boosting AI-Generated Biomedical Images with Confidence through Advanced Statistical Inference.Journal of the American Statistical Association · 2025Article
- A multivariate to multivariate approach for voxel-wise genome-wide association analysis.Statistics in medicine · 2024Article
- Statistical and Machine Learning Analysis in Brain-Imaging Genetics: A Review of Methods.Behavior genetics · 2024Review
- A PARTIALLY FUNCTIONAL LINEAR REGRESSION FRAMEWORK FOR INTEGRATING GENETIC, IMAGING, AND CLINICAL DATA.The annals of applied statistics · 2024Article
- aXonica: A support package for MRI based Neuroimaging.Biotechnology notes (Amsterdam, Netherlands) · 2024Article
- Statistical Learning Methods for Neuroimaging Data Analysis with Applications.Annual review of biomedical data science · 2023Review
- Neuroimaging feature extraction using a neural network classifier for imaging genetics.BMC bioinformatics · 2023Article
- Brain structure and allelic associations in Alzheimer's disease.CNS neuroscience & therapeutics · 2023Article
- Genetic underpinnings of brain structural connectome for young adults.Journal of the American Statistical Association · 2023Article
- Integrative Bayesian tensor regression for imaging genetics applications.Frontiers in neuroscience · 2023Article
- Orthogonalized Kernel Debiased Machine Learning for Multimodal Data Analysis.Journal of the American Statistical Association · 2023Article
- Two-stage linked component analysis for joint decomposition of multiple biologically related data sets.Biostatistics (Oxford, England) · 2022Article
- Deep phenotyping for precision medicine in Parkinson's disease.Disease models & mechanisms · 2022Article
- Multimodal data integration via mediation analysis with high-dimensional exposures and mediators.Human brain mapping · 2022Article
- Image Genetic Analysis and Application Research Based on QRFPR and Other Neural Network-Related SNP Loci.BioMed research international · 2022Article
- Imaging Genetic Based Mediation Analysis for Human Cognition.Frontiers in neuroscience · 2022Article
- Ridge Penalization in High-Dimensional Testing With Applications to Imaging Genetics.Frontiers in neuroscience · 2022Article
- Multivariate Analysis and Modelling of multiple Brain endOphenotypes: Let's MAMBO!Computational and structural biotechnology journal · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 3 institutions in 2 countries.
Funding
Abstract
With the rapid growth of modern technology, many biomedical studies are being conducted to collect massive datasets with volumes of multi-modality imaging, genetic, neurocognitive, and clinical information from increasingly large cohorts. Simultaneously extracting and integrating rich and diverse heterogeneous information in neuroimaging and/or genomics from these big datasets could transform our understanding of how genetic variants impact brain structure and function, cognitive function, and brain-related disease risk across the lifespan. Such understanding is critical for diagnosis, prevention, and treatment of numerous complex brain-related disorders (e.g., schizophrenia and Alzheimer's disease). However, the development of analytical methods for the joint analysis of both high-dimensional imaging phenotypes and high-dimensional genetic data, a big data squared (BD
Indexed as
Identifiers
What 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.