Evidence map›Paper›PMID 10835299›Full record

ArticleAmerican journal of human genetics2000

Bayesian fine-scale mapping of disease loci, by hidden Markov models.

A P Morris, J C Whittaker, D J Balding

Open access · bronzeAbstract read
In one paragraph

Article in American journal of human genetics, 2000. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
10.5field-weighted citation impact, top 1% of its field
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

28 citing papers in PubMed, 88 citations in OpenAlex.

  1. Article
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  4. The limits of fine-scale mapping.Genetic epidemiology · 2009
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  16. Genetic epidemiology, genetic maps and positional cloning.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2003
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

A P MorrisDepartment of Applied Statistics, University of Reading, United Kingdom. sns98am@reading.ac.uk
J C Whittaker
D J Balding
University of Reading · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We present a new multilocus method for the fine-scale mapping of genes contributing to human diseases. The method is designed for use with multiple biallelic markers-in particular, single-nucleotide polymorphisms for which high-density genetic maps will soon be available. We model disease-marker association in a candidate region via a hidden Markov process and allow for correlation between linked marker loci. Using Markov-chain-Monte Carlo simulation methods, we obtain posterior distributions of model parameter estimates including disease-gene location and the age of the disease-predisposing mutation. In addition, we allow for heterogeneity in recombination rates, across the candidate region, to account for recombination hot and cold spots. We also obtain, for the ancestral marker haplotype, a posterior distribution that is unique to our method and that, unlike maximum-likelihood estimation, can properly account for uncertainty. We apply the method to data for cystic fibrosis and Huntington disease, for which mutations in disease genes have already been identified. The new method performs well compared with existing multi-locus mapping methods.

Indexed as

Markov ChainsAllelesBayes TheoremChromosome MappingCystic FibrosisGene FrequencyGenetic Diseases, InbornGenetic LinkageHaplotypesHumansHuntington DiseaseKineticsLikelihood FunctionsModels, GeneticMutationOdds Ratio

Identifiers

PMID10835299
PMCPMC1287074
OpenAlexW2007781696

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.