ArticleJournal of probability and statistics2012
Methods for Analyzing Multivariate Phenotypes in Genetic Association Studies.
Article in Journal of probability and statistics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 68 papers, 4 of them syntheses that pooled it.
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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.
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Who cites it
68 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Integration ofFrontiers in immunology · 2023Pooled it
- Leveraging pleiotropic association using sparse group variable selection in genomics data.BMC medical research methodology · 2022Pooled it
- The association of obesity and coronary artery disease genes with response to SSRIs treatment in major depression.Journal of neural transmission (Vienna, Austria : 1996) · 2019Pooled it
- Multitrait genome association analysis identifies new susceptibility genes for human anthropometric variation in the GCAT cohort.Journal of medical genetics · 2018Pooled it
- Association of Polygenic Score for Schizophrenia and HLA Antigen and Inflammation Genes With Response to Lithium in Bipolar Affective Disorder: A Genome-Wide Association Study.JAMA psychiatry · 2018Trial
- A novel association test for multiple secondary phenotypes from a case-control GWAS.Genetic epidemiology · 2017Trial
- Network construction using sparse Gaussian graphical model based on GWAS summary statistics.Scientific reports · 2025Article
- A novel method for multiple phenotype association studies based on genotype and phenotype network.PLoS genetics · 2024Article
- Joint analysis of multiple phenotypes for extremely unbalanced case-control association studies using multi-layer network.Bioinformatics (Oxford, England) · 2023Article
- A copula-based set-variant association test for bivariate continuous, binary or mixed phenotypes.The international journal of biostatistics · 2023Article
- Simultaneous modeling of multivariate heterogeneous responses and heteroskedasticity via a two-stage composite likelihood.Biometrical journal. Biometrische Zeitschrift · 2023Article
- A clustering linear combination method for multiple phenotype association studies based on GWAS summary statistics.Scientific reports · 2023Article
- Multivariate phenotype analysis enables genome-wide inference of mammalian gene function.PLoS biology · 2022Article
- Blood and brain transcriptome analysis reveals APOE genotype-mediated and immune-related pathways involved in Alzheimer disease.Alzheimer's research & therapy · 2022Article
- A Novel Hierarchical Clustering Approach for Joint Analysis of Multiple Phenotypes Uncovers Obesity Variants Based on ARIC.Frontiers in genetics · 2022Article
- Understanding the metabolome and metagenome as extended phenotypes: The next frontier in macroalgae domestication and improvement.Journal of the World Aquaculture Society · 2021Article
- Identifying genetic risk variants associated with brain volumetric phenotypes via K-sample Ball Divergence method.Genetic epidemiology · 2021Article
- A Novel Approach Integrating Hierarchical Clustering and Weighted Combination for Association Study of Multiple Phenotypes and a Genetic Variant.Frontiers in genetics · 2021Article
- Associating Multivariate Traits with Genetic Variants Using Collapsing and Kernel Methods with Pedigree- or Population-Based Studies.Computational and mathematical methods in medicine · 2021Article
- Article
8 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Multivariate phenotypes are frequently encountered in genetic association studies. The purpose of analyzing multivariate phenotypes usually includes discovery of novel genetic variants of pleiotropy effects, that is, affecting multiple phenotypes, and the ultimate goal of uncovering the underlying genetic mechanism. In recent years, there have been new method development and application of existing statistical methods to such phenotypes. In this paper, we provide a review of the available methods for analyzing association between a single marker and a multivariate phenotype consisting of the same type of components (e.g., all continuous or all categorical) or different types of components (e.g., some are continuous and others are categorical). We also reviewed causal inference methods designed to test whether the detected association with the multivariate phenotype is truly pleiotropy or the genetic marker exerts its effects on some phenotypes through affecting the others.
Identifiers
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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.