Evidence map›Paper›PMID 19215730›Full record

ArticleAmerican journal of human genetics2009

Genotype-imputation accuracy across worldwide human populations.

Lucy Huang, Yun Li, Andrew B Singleton, John A Hardy, Gonçalo Abecasis, Noah A Rosenberg, Paul Scheet

Abstract read
In one paragraph

Article in American journal of human genetics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 172 papers, 13 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
172citing papers in PubMed, 13 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

172 citing papers in PubMed, 13 syntheses or guidelines pooled it.

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  14. Twins, tissue, and time: an assessment of SNPs and CNVs.Twin research and human genetics : the official journal of the International Society for Twin Studies · 2012
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112 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

7 authors.

Lucy HuangDepartment of Biostatistics, University of Michigan, Ann Arbor, MI 48109, USA. hlucy@umich.edu
Yun Li
Andrew B Singleton
John A Hardy
Gonçalo Abecasis
Noah A Rosenberg
Paul Scheet

Funding

Characterization of Normal Genomic VariabilityZIAAG000932 · NIA · NATIONAL INSTITUTE ON AGING · PI SINGLETON, ANDREW · 2009 to 2024
$11.3M
Genome wide SNP analysis in Parkinson's diseaseZ01AG000949 · NIA · NATIONAL INSTITUTE ON AGING · PI SINGLETON, ANDREW B · 2006 to 2008
$2.6M
Population-Genetic Studies for Association MappingR01GM081441 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ROSENBERG, NOAH · 2007 to 2011
$1.7M
Computational Statistic Approaches to Gene-Environment InteractionR01HL090564 · NHLBI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ZOELLNER, SEBASTIAN · 2007 to 2009
$1.1M
Integrated Parametric and Non-parametric Mapping for Genome-Wife Association DataU01HL084729 · NHLBI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ABECASIS, GONCALO · 2006 to 2008
$872k
SICKLE CELL HEMOGLOBIN IN CONCENTRATED TERNARY SOLUTIONSF32HL008472 · NHLBI · BRANDEIS UNIVERSITY · PI MADDEN, THOMAS L · 1991 to 1992
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Intramural NIH HHS Z01 AG000949Medical Research Council G0701075NHLBI NIH HHS R01 HL090564NHLBI NIH HHS U01 HL08472NHLBI NIH HHS U01 HL084729NIGMS NIH HHS R01 GM081441Parkinson's UK G-0907
6 · The paper itself

Abstract

A current approach to mapping complex-disease-susceptibility loci in genome-wide association (GWA) studies involves leveraging the information in a reference database of dense genotype data. By modeling the patterns of linkage disequilibrium in a reference panel, genotypes not directly measured in the study samples can be imputed and tested for disease association. This imputation strategy has been successful for GWA studies in populations well represented by existing reference panels. We used genotypes at 513,008 autosomal single-nucleotide polymorphism (SNP) loci in 443 unrelated individuals from 29 worldwide populations to evaluate the "portability" of the HapMap reference panels for imputation in studies of diverse populations. When a single HapMap panel was leveraged for imputation of randomly masked genotypes, European populations had the highest imputation accuracy, followed by populations from East Asia, Central and South Asia, the Americas, Oceania, the Middle East, and Africa. For each population, we identified "optimal" mixtures of reference panels that maximized imputation accuracy, and we found that in most populations, mixtures including individuals from at least two HapMap panels produced the highest imputation accuracy. From a separate survey of additional SNPs typed in the same samples, we evaluated imputation accuracy in the scenario in which all genotypes at a given SNP position were unobserved and were imputed on the basis of data from a commercial "SNP chip," again finding that most populations benefited from the use of combinations of two or more HapMap reference panels. Our results can serve as a guide for selecting appropriate reference panels for imputation-based GWA analysis in diverse populations.

Indexed as

Genetics, MedicalGenetic VariationGenome-Wide Association StudyGenotypePolymorphism, Single NucleotideAsian PeopleBlack PeopleChromosome MappingHumansLinkage DisequilibriumReproducibility of ResultsSensitivity and SpecificityWhite People

Identifiers

PMID19215730
PMCPMC2668016

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.