Evidence map›Paper›PMID 28401899›Full record

ArticleEuropean journal of human genetics : EJHG2017

Improved imputation accuracy of rare and low-frequency variants using population-specific high-coverage WGS-based imputation reference panel.

Mario Mitt, Mart Kals, Kalle Pärn, Stacey B Gabriel, Eric S Lander, Aarno Palotie, Samuli Ripatti, Andrew P Morris, Andres Metspalu, Tõnu Esko and 2 more

Abstract read
In one paragraph

Article in European journal of human genetics : EJHG, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 159 papers, 22 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
159citing papers in PubMed, 22 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

159 citing papers in PubMed, 22 syntheses or guidelines pooled it.

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99 more citing papers are in PubMed but not listed here.

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

12 authors.

Mario MittEstonian Genome Center, University of Tartu, Tartu, Estonia.
Mart KalsEstonian Genome Center, University of Tartu, Tartu, Estonia.
Kalle PärnEstonian Genome Center, University of Tartu, Tartu, Estonia.
Stacey B GabrielBroad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.
Eric S LanderBroad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.
Aarno PalotieInstitute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.
Samuli RipattiInstitute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.
Andrew P MorrisEstonian Genome Center, University of Tartu, Tartu, Estonia.
Andres MetspaluEstonian Genome Center, University of Tartu, Tartu, Estonia.
Tõnu EskoEstonian Genome Center, University of Tartu, Tartu, Estonia.
Reedik MägiEstonian Genome Center, University of Tartu, Tartu, Estonia.
Priit PaltaEstonian Genome Center, University of Tartu, Tartu, Estonia.

Funding

Wellcome Trust 098017
6 · The paper itself

Abstract

Genetic imputation is a cost-efficient way to improve the power and resolution of genome-wide association (GWA) studies. Current publicly accessible imputation reference panels accurately predict genotypes for common variants with minor allele frequency (MAF)≥5% and low-frequency variants (0.5≤MAF<5%) across diverse populations, but the imputation of rare variation (MAF<0.5%) is still rather limited. In the current study, we evaluate imputation accuracy achieved with reference panels from diverse populations with a population-specific high-coverage (30 ×) whole-genome sequencing (WGS) based reference panel, comprising of 2244 Estonian individuals (0.25% of adult Estonians). Although the Estonian-specific panel contains fewer haplotypes and variants, the imputation confidence and accuracy of imputed low-frequency and rare variants was significantly higher. The results indicate the utility of population-specific reference panels for human genetic studies.

Indexed as

Gene FrequencyGenome, HumanPolymorphism, Single NucleotideFemaleGenome-Wide Association StudyHaplotypesHumansMaleReference StandardsSequence Analysis, DNA

Identifiers

PMID28401899
PMCPMC5520064

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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.