ArticleBMC proceedings2009
Genome-wide gene-based association study.
Article in BMC proceedings, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
What it found
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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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Significant association between TAP2 polymorphisms and rheumatoid arthritis: a meta-analysis.Diagnostic pathology · 2014Pooled it
- Identifying prioritization of therapeutic targets for ankylosing spondylitis: a multi-omics Mendelian randomization study.Journal of translational medicine · 2024Article
- Gene-Based Genome-Wide Association Study Identified Genes for Agronomic Traits in Maize.Biology · 2022Article
- OPATs: Omnibus P-value association tests.Briefings in bioinformatics · 2019Review
- Association of BTNL2 single nucleotide polymorphisms with knee osteoarthritis susceptibility.International journal of clinical and experimental pathology · 2019Article
- Knowledge-based analysis of genetic associations of rheumatoid arthritis to inform studies searching for pleiotropic genes: a literature review and network analysis.Arthritis research & therapy · 2015Review
- Applying genome-wide gene-based expression quantitative trait locus mapping to study population ancestry and pharmacogenetics.BMC genomics · 2014Article
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- Article
- Region-based and pathway-based QTL mapping using a p-value combination method.BMC proceedings · 2011Article
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- GATES: a rapid and powerful gene-based association test using extended Simes procedure.American journal of human genetics · 2011Article
- Gene- or region-based analysis of genome-wide association studies.Genetic epidemiology · 2009Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Genome-wide association studies, which analyzes hundreds of thousands of single-nucleotide polymorphisms to identify disease susceptibility genes, are challenging because the work involves intensive computation and complex modeling. We propose a two-stage genome-wide association scanning procedure, consisting of a single-locus association scan for the first stage and a gene-based association scan for the second stage. Marginal effects of single-nucleotide polymorphisms are examined by using the exact Armitage trend test or logistic regression, and gene effects are examined by using a p-value combination method. Compared with some existing single-locus and multilocus methods, the proposed method has the following merits: 1) convenient for definition of biologically meaningful regions, 2) powerful for detection of minor-effect genes, 3) helpful for alleviation of a multiple-testing problem, and 4) convenient for result interpretation. The method was applied to study Genetic Analysis Workshop 16 Problem 1 rheumatoid arthritis data, and strong association signals were found. The results show that the human major histocompatibility complex region is the most important genomic region associated with rheumatoid arthritis. Moreover, previously reported genes including PTPN22, C5, and IL2RB were confirmed; novel genes including HLA-DRA, BTNL2, C6orf10, NOTCH4, TAP2, and TNXB were identified by our analysis.
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.