ArticleFrontiers in genetics2021
An Omnibus Test for Detecting Multiple Phenotype Associations Based on GWAS Summary Level Data.
Article in Frontiers in genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 8 citations in OpenAlex.
- MIRAGE: A Bayesian statistical method for gene-level rare-variant analysis incorporating functional annotations.American journal of human genetics · 2026Article
- Genomic insights into stroke recovery: cross-phenotype associations.Brain communications · 2026Article
- A multi-trait epigenome-wide association study identified DNA methylation signature of inflammation among men with HIV.Clinical epigenetics · 2024Article
- A multi-trait epigenome-wide association study identified DNA methylation signature of inflammation among people with HIV.Research square · 2024Article
- Genome-Wide Network Analysis of Above- and Below-Ground Co-growth inPlant phenomics (Washington, D.C.) · 2024Article
- Investigating causality and shared genetic architecture between body mass index and cognitive function: a genome-wide cross-trait analysis and bi-directional Mendelian randomization study.Frontiers in aging neuroscience · 2024Article
- Article
- Recent advances and challenges of rare variant association analysis in the biobank sequencing era.Frontiers in genetics · 2022Review
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Abundant Genome-wide association study (GWAS) findings have reflected the sharing of genetic variants among multiple phenotypes. Exploring the association between genetic variants and multiple traits can provide novel insights into the biological mechanism of complex human traits. In this article, we proposed to apply the generalized Berk-Jones (GBJ) test and the generalized higher criticism (GHC) test to identify the genetic variants that affect multiple traits based on GWAS summary statistics. To be more robust to different gene-multiple traits association patterns across the whole genome, we proposed an omnibus test (OMNI) by using the aggregated Cauchy association test. We conducted extensive simulation studies to investigate the type one error rates and compare the powers of the proposed tests (i.e., the GBJ, GHC and OMNI tests) and the existing tests (i.e., the minimum of the
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