ArticlePloS one2011
Joint analysis for genome-wide association studies in family-based designs.
Article in PloS one, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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Who cites it
7 citing papers in PubMed, 14 citations in OpenAlex.
- A novel method for multiple phenotype association studies based on genotype and phenotype network.PLoS genetics · 2024Article
- A clustering linear combination method for multiple phenotype association studies based on GWAS summary statistics.Scientific reports · 2023Article
- A computationally efficient clustering linear combination approach to jointly analyze multiple phenotypes for GWAS.PloS one · 2022Article
- A clustering linear combination approach to jointly analyze multiple phenotypes for GWAS.Bioinformatics (Oxford, England) · 2019Article
- A multiple regression method for genomewide association studies using only linkage information.Journal of genetics · 2018Article
- On family-based genome-wide association studies with large pedigrees: observations and recommendations.BMC proceedings · 2014Article
- Detecting association of rare variants by testing an optimally weighted combination of variants for quantitative traits in general families.Annals of human genetics · 2013Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
Abstract
In family-based data, association information can be partitioned into the between-family information and the within-family information. Based on this observation, Steen et al. (Nature Genetics. 2005, 683-691) proposed an interesting two-stage test for genome-wide association (GWA) studies under family-based designs which performs genomic screening and replication using the same data set. In the first stage, a screening test based on the between-family information is used to select markers. In the second stage, an association test based on the within-family information is used to test association at the selected markers. However, we learn from the results of case-control studies (Skol et al. Nature Genetics. 2006, 209-213) that this two-stage approach may be not optimal. In this article, we propose a novel two-stage joint analysis for GWA studies under family-based designs. For this joint analysis, we first propose a new screening test that is based on the between-family information and is robust to population stratification. This new screening test is used in the first stage to select markers. Then, a joint test that combines the between-family information and within-family information is used in the second stage to test association at the selected markers. By extensive simulation studies, we demonstrate that the joint analysis always results in increased power to detect genetic association and is robust to population stratification.
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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.