ArticlePloS one2018
A novel method to test associations between a weighted combination of phenotypes and genetic variants.
Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Principal component analysis revisited: fast multitrait genetic evaluations with smooth convergence.G3 (Bethesda, Md.) · 2024Article
- Gene-based association tests using GWAS summary statistics and incorporating eQTL.Scientific reports · 2022Article
- A computationally efficient clustering linear combination approach to jointly analyze multiple phenotypes for GWAS.PloS one · 2022Article
- Associating Multivariate Traits with Genetic Variants Using Collapsing and Kernel Methods with Pedigree- or Population-Based Studies.Computational and mathematical methods in medicine · 2021Article
- A Novel Approach Integrating Hierarchical Clustering and Weighted Combination for Association Study of Multiple Phenotypes and a Genetic Variant.Frontiers in genetics · 2021Article
- A flexible and nearly optimal sequential testing approach to randomized testing: QUICK-STOP.Genetic epidemiology · 2020Article
- Joint analysis of multiple phenotypes using a clustering linear combination method based on hierarchical clustering.Genetic epidemiology · 2020Article
- Discovering network phenotype between genetic risk factors and disease status via diagnosis-aligned multi-modality regression method in Alzheimer's disease.Bioinformatics (Oxford, England) · 2019Article
- Joint Analysis of Multiple Phenotypes in Association Studies based on Cross-Validation Prediction Error.Scientific reports · 2019Article
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Authors and funding
3 authors.
Funding
Abstract
Many complex diseases like diabetes, hypertension, metabolic syndrome, et cetera, are measured by multiple correlated phenotypes. However, most genome-wide association studies (GWAS) focus on one phenotype of interest or study multiple phenotypes separately for identifying genetic variants associated with complex diseases. Analyzing one phenotype or the related phenotypes separately may lose power due to ignoring the information obtained by combining phenotypes, such as the correlation between phenotypes. In order to increase statistical power to detect genetic variants associated with complex diseases, we develop a novel method to test a weighted combination of multiple phenotypes (WCmulP). We perform extensive simulation studies as well as real data (COPDGene) analysis to evaluate the performance of the proposed method. Our simulation results show that WCmulP has correct type I error rates and is either the most powerful test or comparable to the most powerful test among the methods we compared. WCmulP also has an outstanding performance for identifying single-nucleotide polymorphisms (SNPs) associated with COPD-related phenotypes.
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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.