ArticleGenetic epidemiology2012
A novel bayesian graphical model for genome-wide multi-SNP association mapping.
Article in Genetic epidemiology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
19 citing papers in PubMed, 1 synthesis or guideline pooled it, 44 citations in OpenAlex.
- Detecting fitness epistasis in recently admixed populations with genome-wide data.BMC genomics · 2020Pooled it
- RIL-StEp: epistasis analysis of rice recombinant inbred lines reveals candidate interacting genes that control seed hull color and leaf chlorophyll content.G3 (Bethesda, Md.) · 2021Article
- Facilitating Anti-Cancer Combinatorial Drug Discovery by Targeting Epistatic Disease Genes.Molecules (Basel, Switzerland) · 2018Article
- Bayesian analysis of genome-wide inflammatory bowel disease data sets reveals new risk loci.European journal of human genetics : EJHG · 2018Article
- Bayesian Approximate Kernel Regression with Variable Selection.Journal of the American Statistical Association · 2018Article
- Computational methods using genome-wide association studies to predict radiotherapy complications and to identify correlative molecular processes.Scientific reports · 2017Article
- Multi-locus Test and Correction for Confounding Effects in Genome-Wide Association Studies.The international journal of biostatistics · 2016Article
- A BAYESIAN GRAPHICAL MODEL FOR GENOME-WIDE ASSOCIATION STUDIES (GWAS).The annals of applied statistics · 2016Article
- Functional Regression Models for Epistasis Analysis of Multiple Quantitative Traits.PLoS genetics · 2016Article
- JBASE: Joint Bayesian Analysis of Subphenotypes and Epistasis.Bioinformatics (Oxford, England) · 2016Article
- The Prediction of Radiotherapy Toxicity Using Single Nucleotide Polymorphism-Based Models: A Step Toward Prevention.Seminars in radiation oncology · 2015Review
- Bayesian Partition Models for Identifying Expression Quantitative Trait Loci.Journal of the American Statistical Association · 2015Article
- Evaluating methods for modeling epistasis networks with application to head and neck cancer.Cancer informatics · 2015Article
- A Bayesian Partitioning Model for the Detection of Multilocus Effects in Case-Control Studies.Human heredity · 2015Article
- Detecting epistasis in human complex traits.Nature reviews. Genetics · 2014Review
- Article
- Personalised nutrition: how far has nutrigenomics progressed?European journal of clinical nutrition · 2013Review
- Using Bayesian networks to discover relations between genes, environment, and disease.BioData mining · 2013Article
- Reprioritizing genetic associations in hit regions using LASSO-based resample model averaging.Genetic epidemiology · 2012Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author at 1 institution in 1 country.
Funding
Abstract
Most disease association mapping algorithms are based on hypothesis testing procedures that test one variant at a time. Those methods lose power when the disease mutations are jointly tagged by multiple variants, or when gene-gene interaction exist. Nearby variants are also correlated, for which procedures ignoring the dependence between variants will inevitably produce redundant results. With a large number of variants genotyped in current genome-wide disease association studies, simultaneous multivariant association mapping algorithms are strongly desired. We present a novel Bayesian method for automatic detection of multivariant joint association in genome-wide case-control studies. Our method has improved power and specificity over existing tools. We fit a joint probabilistic model to the entire data and identify disease variants simultaneously. The method dynamically accounts for the strong linkage disequilibrium (LD) between variants. As a result, only the primary disease variants will be identified, with all secondary associations due to LD effects filtered out. Our method better pinpoints the disease variants with improved resolution. The method is also computationally efficient for genome-wide studies. When applied to a real data set of inflammatory bowel disease (IBD) containing 401,473 variants in 4,720 individuals, our method detected all previously reported IBD loci in the same data, and recovered two missed loci. We further detected two novel interchromosome interactions. The first is between STAT3 and PARD6G, and the second is between DLG5 and an intergenic region at 5p14. We further validated the two interactions in an independent study.
Indexed as
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.