Evidence map›Paper›PMID 37388906›Full record

ArticleCell genomics2023

Performance and accuracy evaluation of reference panels for genotype imputation in sub-Saharan African populations.

Dhriti Sengupta, Gerrit Botha, Ayton Meintjes, Mamana Mbiyavanga, AWI-Gen Study, H3Africa Consortium, Scott Hazelhurst, Nicola Mulder, Michèle Ramsay, Ananyo Choudhury

Abstract read
In one paragraph

Article in Cell genomics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 2 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

24 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  20. Imputation accuracy across global human populations.American journal of human genetics · 2024
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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.

Dhriti SenguptaSydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
Gerrit BothaComputational Biology Division, Department of Integrative Biomedical Sciences, Institute for Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa.
Ayton MeintjesComputational Biology Division, Department of Integrative Biomedical Sciences, Institute for Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa.
Mamana MbiyavangaComputational Biology Division, Department of Integrative Biomedical Sciences, Institute for Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa.
AWI-Gen Study
H3Africa Consortium
Scott HazelhurstSydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
Nicola MulderComputational Biology Division, Department of Integrative Biomedical Sciences, Institute for Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa.
Michèle RamsaySydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
Ananyo ChoudhurySydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Based on evaluations of imputation performed on a genotype dataset consisting of about 11,000 sub-Saharan African (SSA) participants, we show Trans-Omics for Precision Medicine (TOPMed) and the African Genome Resource (AGR) to be currently the best panels for imputing SSA datasets. We report notable differences in the number of single-nucleotide polymorphisms (SNPs) that are imputed by different panels in datasets from East, West, and South Africa. Comparisons with a subset of 95 SSA high-coverage whole-genome sequences (WGSs) show that despite being about 20-fold smaller, the AGR imputed dataset has higher concordance with the WGSs. Moreover, the level of concordance between imputed and WGS datasets was strongly influenced by the extent of Khoe-San ancestry in a genome, highlighting the need for integration of not only geographically but also ancestrally diverse WGS data in reference panels for further improvement in imputation of SSA datasets. Approaches that integrate imputed data from different panels could also lead to better imputation.

Indexed as

AfricaAGRGWASimputationimputation accuracynon-reference discordance ratereference panelTOPMedwhole-genome sequence

Identifiers

PMID37388906
PMCPMC10300601

What Socratic holds

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LicenceCC BY-NC-ND
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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 Socratic graph.