Evidence map›Paper›PMID 15342541›Full record

ArticleGenetics2004

Application of coalescent methods to reveal fine-scale rate variation and recombination hotspots.

Paul Fearnhead, Rosalind M Harding, Julie A Schneider, Simon Myers, Peter Donnelly

Abstract read
In one paragraph

Article in Genetics, 2004. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed, 5 pooled it
–field-weighted citation impact
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

29 citing papers in PubMed, 5 syntheses or guidelines pooled it.

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  10. Fine-scale variation in meiotic recombination in Mimulus inferred from population shotgun sequencing.Proceedings of the National Academy of Sciences of the United States of America · 2013
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  16. Contrasting methods of quantifying fine structure of human recombination.Annual review of genomics and human genetics · 2010
    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

5 authors.

Paul FearnheadDepartment of Mathematics and Statistics, Lancaster University, Lancaster LA1 4YF, United Kingdom.
Rosalind M Harding
Julie A Schneider
Simon Myers
Peter Donnelly

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

There has been considerable recent interest in understanding the way in which recombination rates vary over small physical distances, and the extent of recombination hotspots, in various genomes. Here we adapt, apply, and assess the power of recently developed coalescent-based approaches to estimating recombination rates from sequence polymorphism data. We apply full-likelihood estimation to study rate variation in and around a well-characterized recombination hotspot in humans, in the beta-globin gene cluster, and show that it provides similar estimates, consistent with those from sperm studies, from two populations deliberately chosen to have different demographic and selectional histories. We also demonstrate how approximate-likelihood methods can be used to detect local recombination hotspots from genomic-scale SNP data. In a simulation study based on 80 100-kb regions, these methods detect 43 out of 60 hotspots (ranging from 1 to 2 kb in size), with only two false positives out of 2000 subregions that were tested for the presence of a hotspot. Our study suggests that new computational tools for sophisticated analysis of population diversity data are valuable for hotspot detection and fine-scale mapping of local recombination rates.

Indexed as

Genetic VariationRecombination, GeneticDNAGenomeGlobinsHaplotypesHumansLikelihood FunctionsModels, GeneticModels, StatisticalDNAGlobins

Identifiers

PMID15342541
PMCPMC1470991

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.