Evidence map›Paper›PMID 23539302›Full record

ArticleBioinformatics (Oxford, England)2013

Improved ancestry inference using weights from external reference panels.

Chia-Yen Chen, Samuela Pollack, David J Hunter, Joel N Hirschhorn, Peter Kraft, Alkes L Price

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 145 papers, 8 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
145citing papers in PubMed, 8 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

145 citing papers in PubMed, 8 syntheses or guidelines pooled it.

  1. Pooled it
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  15. Blood DNA Methylation Predicts Long-Term Risk of Dementia in Prospective Cohorts.medRxiv : the preprint server for health sciences · 2026
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85 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

6 authors.

Chia-Yen ChenDepartment of Epidemiology, Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA. cychen@mail.harvard.edu
Samuela Pollack
David J Hunter
Joel N Hirschhorn
Peter Kraft
Alkes L Price

Funding

Methods for Genome-wide Association Studies in Admixed PopulationsR01HG006399 · NHGRI · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI PRICE, ALKES L · 2011 to 2024
$6.3M
SLEEP AND ENTRAINMENT OF SCN FUNCTIONR01HL064278 · NHLBI · CASE WESTERN RESERVE UNIVERSITY · PI STROHL, KINGMAN PERKINS · 1999 to 2002
$871k
THE FRAMINGHAM HEART STUDY-N01HC25195-268025195-268025195N01HC025195 · HC · TRUSTEES OF BOSTON UNIVERSITY · PI WOLF, PHILIP A · 2002 to 2006
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NHGRI NIH HHS R01 HG006399NHLBI NIH HHS N01 HC025195NHLBI NIH HHS N02 HL064278
6 · The paper itself

Abstract

motivationInference of ancestry using genetic data is motivated by applications in genetic association studies, population genetics and personal genomics. Here, we provide methods and software for improved ancestry inference using genome-wide single nucleotide polymorphism (SNP) weights from external reference panels. This approach makes it possible to leverage the rich ancestry information that is available from large external reference panels, without the administrative and computational complexities of re-analyzing the raw genotype data from the reference panel in subsequent studies.

resultsWe extensively validate our approach in multiple African American, Latino American and European American datasets, making use of genome-wide SNP weights derived from large reference panels, including HapMap 3 populations and 6546 European Americans from the Framingham Heart Study. We show empirically that our approach provides much greater accuracy than either the prevailing ancestry-informative marker (AIM) approach or the analysis of genome-wide target genotypes without a reference panel. For example, in an independent set of 1636 European American genome-wide association study samples, we attained prediction accuracy (R(2)) of 1.000 and 0.994 for the first two principal components using our method, compared with 0.418 and 0.407 using 150 published AIMs or 0.955 and 0.003 by applying principal component analysis directly to the target samples. We finally show that the higher accuracy in inferring ancestry using our method leads to more effective correction for population stratification in association studies. AVAILABILITY: The SNPweights software is available online at http://www.hsph.harvard.edu/faculty/alkes-price/software/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Indexed as

Polymorphism, Single NucleotideBlack or African AmericanGenome-Wide Association StudyGenotypeHapMap ProjectHumansPrincipal Component AnalysisRacial GroupsSoftwareUnited StatesWhite People

Identifiers

PMID23539302
PMCPMC3661048

What OpenQuestion holds

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Read underepoch 390

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.