Evidence map›Paper›PMID 42486871›Full record

ArticleNature communications2026

VN1K is a pangenome-informed multi-omics and phenomics resource for the Vietnamese population.

Trang T H Tran, Tham H Hoang, Mai H Tran, Tien M Pham, Nam N Nguyen, Giang M Vu, Vinh C Duong, Quang T Vu, Nguyen T Nguyen, Hien Q Vu and 33 more

Abstract read
In one paragraph

Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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

1 citing paper in PubMed.

  1. Article
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

43 authors.

Trang T H Tran *VinUni Big Data Research Institute, VinUniversity, Hanoi, Vietnam.
Tham H Hoang *VinUni Big Data Research Institute, VinUniversity, Hanoi, Vietnam.
Mai H TranVinUni Big Data Research Institute, VinUniversity, Hanoi, Vietnam.
Tien M PhamVinUni Big Data Research Institute, VinUniversity, Hanoi, Vietnam.ORCID 0000-0002-3517-1876
Nam N NguyenVinUni Big Data Research Institute, VinUniversity, Hanoi, Vietnam.ORCID 0000-0002-6329-585X
Giang M VuVinUni Big Data Research Institute, VinUniversity, Hanoi, Vietnam.
Vinh C DuongVinUni Big Data Research Institute, VinUniversity, Hanoi, Vietnam.
Quang T VuVinUni Big Data Research Institute, VinUniversity, Hanoi, Vietnam.
Nguyen T NguyenVinUni Big Data Research Institute, VinUniversity, Hanoi, Vietnam.
Hien Q VuVinUni Big Data Research Institute, VinUniversity, Hanoi, Vietnam.ORCID 0000-0002-9259-8382
Trang M NguyenVinUni Big Data Research Institute, VinUniversity, Hanoi, Vietnam.ORCID 0000-0002-0438-8538
Thien K NguyenVinUni Big Data Research Institute, VinUniversity, Hanoi, Vietnam.
Sang V NguyenVinUni Big Data Research Institute, VinUniversity, Hanoi, Vietnam.
Toan DangVinUni Big Data Research Institute, VinUniversity, Hanoi, Vietnam.
Hoang NguyenVinUni Big Data Research Institute, VinUniversity, Hanoi, Vietnam.
Tuan DoVinUni Big Data Research Institute, VinUniversity, Hanoi, Vietnam.
Cuong LeVinUni Big Data Research Institute, VinUniversity, Hanoi, Vietnam.
Dat T NguyenVinUni Big Data Research Institute, VinUniversity, Hanoi, Vietnam.
Hung T T NguyenVinUni Big Data Research Institute, VinUniversity, Hanoi, Vietnam.
Nam Q LeVinUni Big Data Research Institute, VinUniversity, Hanoi, Vietnam.ORCID 0000-0001-9997-5948
Quang-Huy NguyenVinUni Big Data Research Institute, VinUniversity, Hanoi, Vietnam.
Linh T LeVinUni Big Data Research Institute, VinUniversity, Hanoi, Vietnam.
Thang PhamVinUni Big Data Research Institute, VinUniversity, Hanoi, Vietnam.
Duc M VuVinmec - VinUni Institute of Immunology, VinUniversity, Hanoi, Vietnam.ORCID 0000-0001-8932-2142
Huong T T LeResearch Institute of Stem Cell and Gene Technology, College of Health Sciences, VinUniversity, Hanoi, Vietnam.
Tho D NgoNursing Division, Vinmec Healthcare System, Hanoi, Vietnam.
Liem T NguyenResearch Institute of Stem Cell and Gene Technology, College of Health Sciences, VinUniversity, Hanoi, Vietnam.
Yen HoangHanoi Medical University, Hanoi, Vietnam.
Dat X DaoHanoi Medical University, Hanoi, Vietnam.
Giang H PhanHanoi Medical University, Hanoi, Vietnam.ORCID 0009-0005-2068-2840
Thinh TranHanoi Medical University, Hanoi, Vietnam.
Quang TranVinUni Big Data Research Institute, VinUniversity, Hanoi, Vietnam.ORCID 0009-0004-6314-3903
Chi Trung HaVinUni Big Data Research Institute, VinUniversity, Hanoi, Vietnam.ORCID 0000-0001-8413-7263
Loan NguyenQueensland Alliance for Agriculture and Food Innovation, The University of Queensland, Brisbane, QLD, Australia.
Hung N LuuDr. Mary and Ron Neal Cancer Center, Houston Methodist Research Institute, Houston, TX, USA.
Minh DaoVinUni Big Data Research Institute, VinUniversity, Hanoi, Vietnam.
Ly LeVinUni Big Data Research Institute, VinUniversity, Hanoi, Vietnam.
Vinh S LeUniversity of Engineering and Technology, Vietnam National University Hanoi, Hanoi, Vietnam.
Nguyen Thuy DuongVinUni Big Data Research Institute, VinUniversity, Hanoi, Vietnam.
Quan NguyenVinUni Big Data Research Institute, VinUniversity, Hanoi, Vietnam. quan.nguyen@imb.uq.edu.au.ORCID 0000-0001-7870-5703
Duc-Hau LeVinUni Big Data Research Institute, VinUniversity, Hanoi, Vietnam. hauld@soict.hust.edu.vn.ORCID 0000-0002-4951-5916
Van VuVinUni Big Data Research Institute, VinUniversity, Hanoi, Vietnam. van.vh@vinuni.edu.vn.
Nam S VoVinUni Big Data Research Institute, VinUniversity, Hanoi, Vietnam. nam.vs@vinuni.edu.vn.ORCID 0000-0002-5454-9176

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The population of Vietnam remains underrepresented in global genomic databases. Here, we present VN1K, a resource of multi-omics and phenotypic information for 1011 unrelated Vietnamese individuals. We present high-depth short-read whole-genome sequencing data for all samples along with various -omics datasets. Using a high-sensitivity variant detection pipeline, which includes a pangenome graph reference and a deep-learning framework, we identify approximately 42 million variants with 7 million short insertions/deletions and 90 thousand structural variants. VN1K also features a whole-genome methylation profile based on long read sequencing. We create a genotype imputation panel with high accuracy on the Vietnamese population, allowing us to identify variants with significantly different allele frequencies in the Vietnamese population compared to other populations. We establish the functional relevance of some of these variants, particularly those in genes associated with genetic disorders, immune diseases, and drug responses, by integrating the allele frequency differences with known genotype-phenotype associations and clinical annotations. Further, we map various loci related to hepatitis B virus infection, triglyceride levels, LDL-C levels, serum glucose levels, HbA1c levels, and levels of two liver enzymes (ALT and AST). The VN1K dataset is accessible via genome.vinbigdata.org, an integrated platform with both linear and graph-based genome browsers.

Indexed as

Genome, HumanPhenomicsDatabases, GeneticGene FrequencyGenomicsGenotypeHumansMultiomicsPhenotypePolymorphism, Single NucleotideSoutheast Asian PeopleVietnamWhole Genome Sequencing

Identifiers

PMID42486871
PMCPMC13392358

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LicenceCC BY-NC-ND
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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.