ArticleGenetics2005
Coalescent-based association mapping and fine mapping of complex trait loci.
Article in Genetics, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers.
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
62 citing papers in PubMed, 130 citations in OpenAlex.
- Genealogy-based trait association with LOCATER boosts power at loci with allelic heterogeneity.Genome research · 2026Article
- Clade distillation for genome-wide association studies.Genetics · 2026Article
- Tree-based QTL mapping with expected local genetic relatedness matrices.American journal of human genetics · 2023Article
- Using enormous genealogies to map causal variants in space and time.Nature genetics · 2023Article
- Biobank-scale inference of ancestral recombination graphs enables genealogical analysis of complex traits.Nature genetics · 2023Article
- Tree-based QTL mapping with expected local genetic relatedness matrices.bioRxiv : the preprint server for biology · 2023Article
- Efficiently Summarizing Relationships in Large Samples: A General Duality Between Statistics of Genealogies and Genomes.Genetics · 2020Article
- Gene-set association and epistatic analyses reveal complex gene interaction networks affecting flowering time in a worldwide barley collection.Journal of experimental botany · 2019Article
- High-throughput inference of pairwise coalescence times identifies signals of selection and enriched disease heritability.Nature genetics · 2018Article
- Haplotype Heritability Mapping Method Uncovers Missing Heritability of Complex Traits.Scientific reports · 2018Article
- Article
- Sampletrees and Rsampletrees: sampling gene genealogies conditional on SNP genotype data.Bioinformatics (Oxford, England) · 2016Article
- New Genetic Approaches to AD: Lessons from APOE-TOMM40 Phylogenetics.Current neurology and neuroscience reports · 2016Review
- The Decay of Disease Association with Declining Linkage Disequilibrium: A Fine Mapping Theorem.Frontiers in genetics · 2016Article
- Comparing performance of non-tree-based and tree-based association mapping methods.BMC proceedings · 2016Article
- Reflections on the Field of Human Genetics: A Call for Increased Disease Genetics Theory.Frontiers in genetics · 2016Article
- Fine Mapping Causal Variants with an Approximate Bayesian Method Using Marginal Test Statistics.Genetics · 2015Article
- Simultaneous inference of haplotypes and alleles at a causal gene.Frontiers in genetics · 2015Article
- Detecting local haplotype sharing and haplotype association.Genetics · 2014Article
- Bayesian inference of local trees along chromosomes by the sequential Markov coalescent.Journal of molecular evolution · 2014Article
2 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
We outline a general coalescent framework for using genotype data in linkage disequilibrium-based mapping studies. Our approach unifies two main goals of gene mapping that have generally been treated separately in the past: detecting association (i.e., significance testing) and estimating the location of the causative variation. To tackle the problem, we separate the inference into two stages. First, we use Markov chain Monte Carlo to sample from the posterior distribution of coalescent genealogies of all the sampled chromosomes without regard to phenotype. Then, averaging across genealogies, we estimate the likelihood of the phenotype data under various models for mutation and penetrance at an unobserved disease locus. The essential signal that these models look for is that in the presence of disease susceptibility variants in a region, there is nonrandom clustering of the chromosomes on the tree according to phenotype. The extent of nonrandom clustering is captured by the likelihood and can be used to construct significance tests or Bayesian posterior distributions for location. A novelty of our framework is that it can naturally accommodate quantitative data. We describe applications of the method to simulated data and to data from a Mendelian locus (CFTR, responsible for cystic fibrosis) and from a proposed complex trait locus (calpain-10, implicated in type 2 diabetes).
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.