Evidence map›Paper›PMID 37524845›Full record

ArticleScientific reports2023

A diverse ancestrally-matched reference panel increases genotype imputation accuracy in a underrepresented population.

John Mauleekoonphairoj, Sissades Tongsima, Apichai Khongphatthanayothin, Sean J Jurgens, Dominic S Zimmerman, Boosamas Sutjaporn, Pharawee Wandee, Connie R Bezzina, Koonlawee Nademanee, Yong Poovorawan

Abstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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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

4 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

10 authors.

John MauleekoonphairojCenter of Excellence in Arrhythmia Research, Department of Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand.
Sissades TongsimaNational Biobank of Thailand, National Science and Technology Development Agency, Pathum Thani, Thailand.
Apichai KhongphatthanayothinCenter of Excellence in Arrhythmia Research, Department of Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand.
Sean J JurgensHeart Center, Department of Experimental Cardiology, Amsterdam Cardiovascular Sciences, Amsterdam University, Medical Centre, University of Amsterdam, Amsterdam, The Netherlands.
Dominic S ZimmermanHeart Center, Department of Experimental Cardiology, Amsterdam Cardiovascular Sciences, Amsterdam University, Medical Centre, University of Amsterdam, Amsterdam, The Netherlands.
Boosamas SutjapornCenter of Excellence in Arrhythmia Research, Department of Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand.
Pharawee WandeeCenter of Excellence in Arrhythmia Research, Department of Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand.
Connie R BezzinaHeart Center, Department of Experimental Cardiology, Amsterdam Cardiovascular Sciences, Amsterdam University, Medical Centre, University of Amsterdam, Amsterdam, The Netherlands.
Koonlawee NademaneeCenter of Excellence in Arrhythmia Research, Department of Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand.
Yong PoovorawanCenter of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand. yong.p@chula.ac.th.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Variant imputation, a common practice in genome-wide association studies, relies on reference panels to infer unobserved genotypes. Multiple public reference panels are currently available with variations in size, sequencing depth, and represented populations. Currently, limited data exist regarding the performance of public reference panels when used in an imputation of populations underrepresented in the reference panel. Here, we compare the performance of various public reference panels: 1000 Genomes Project, Haplotype Reference Consortium, GenomeAsia 100 K, and the recent Trans-Omics for Precision Medicine (TOPMed) program, when used in an imputation of samples from the Thai population. Genotype yields were assessed, and imputation accuracies were examined by comparison with high-depth whole genome sequencing data of the same sample. We found that imputation using the TOPMed panel yielded the largest number of variants (~ 271 million). Despite being the smallest in size, GenomeAsia 100 K achieved the best imputation accuracy with a median genotype concordance rate of 0.97. For rare variants, GenomeAsia 100 K also offered the best accuracy, although rare variants were less accurately imputable than common variants (30.3% reduction in concordance rates). The high accuracy observed when using GenomeAsia 100 K is likely attributable to the diverse representation of populations genetically similar to the study cohort emphasizing the benefits of sequencing populations classically underrepresented in human genomics.

Indexed as

Genome-Wide Association StudyPolymorphism, Single NucleotideGene FrequencyGenome, HumanGenotypeHaplotypesHumans

Identifiers

PMID37524845
PMCPMC10390539

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