Evidence map›Paper›PMID 23874685›Full record

ArticlePloS one2013

Local exome sequences facilitate imputation of less common variants and increase power of genome wide association studies.

Peter K Joshi, James Prendergast, Ross M Fraser, Jennifer E Huffman, Veronique Vitart, Caroline Hayward, Ruth McQuillan, Dominik Glodzik, Ozren Polašek, Nicholas D Hastie and 6 more

Abstract read
In one paragraph

Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–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

11 citing papers in PubMed.

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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

16 authors.

Peter K JoshiCentre for Population Health Sciences, University of Edinburgh, Edinburgh, Scotland, United Kingdom.
James Prendergast
Ross M Fraser
Jennifer E Huffman
Veronique Vitart
Caroline Hayward
Ruth McQuillan
Dominik Glodzik
Ozren Polašek
Nicholas D Hastie
Igor Rudan
Harry Campbell
Alan F Wright
Chris S Haley
James F Wilson
Pau Navarro

Funding

Chief Scientist Office CZB/4/710Medical Research Council MC_PC_U127561128Medical Research Council MC_PC_U127592696Medical Research Council MC_U127592696Wellcome Trust 095831
6 · The paper itself

Abstract

The analysis of less common variants in genome-wide association studies promises to elucidate complex trait genetics but is hampered by low power to reliably detect association. We show that addition of population-specific exome sequence data to global reference data allows more accurate imputation, particularly of less common SNPs (minor allele frequency 1-10%) in two very different European populations. The imputation improvement corresponds to an increase in effective sample size of 28-38%, for SNPs with a minor allele frequency in the range 1-3%.

Indexed as

ExomeGene FrequencyGenome, HumanGenome-Wide Association StudyGenotypeHumansPolymorphism, Single NucleotideWhite People

Identifiers

PMID23874685
PMCPMC3712964

What OpenQuestion holds

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Registered trials

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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.