ArticleBMC genomics2021
Mid-pass whole genome sequencing enables biomedical genetic studies of diverse populations.
Article in BMC genomics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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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.
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Who cites it
7 citing papers in PubMed, 17 citations in OpenAlex.
- Article
- Meta-analysis of over 8,000 individuals from Hawai'i and Samoa for genetic associations to cardiometabolic phenotypes.medRxiv : the preprint server for health sciences · 2026Article
- A map of blood regulatory variation in South Africans enables GWAS interpretation.Nature genetics · 2025Article
- A rare splice-site variant in TNNT2: the need for ancestral diversity in genomic reference data sets.European heart journal · 2025Article
- Hyperuricaemia and gout in the Pacific.Nature reviews. Rheumatology · 2025Review
- Principles and methods for transferring polygenic risk scores across global populations.Nature reviews. Genetics · 2024Review
- A PolynesianHGG advances · 2023Article
Corrections and comments
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Authors and funding
17 authors at 5 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundHistorically, geneticists have relied on genotyping arrays and imputation to study human genetic variation. However, an underrepresentation of diverse populations has resulted in arrays that poorly capture global genetic variation, and a lack of reference panels. This has contributed to deepening global health disparities. Whole genome sequencing (WGS) better captures genetic variation but remains prohibitively expensive. Thus, we explored WGS at "mid-pass" 1-7x coverage.
resultsHere, we developed and benchmarked methods for mid-pass sequencing. When applied to a population without an existing genomic reference panel, 4x mid-pass performed consistently well across ethnicities, with high recall (98%) and precision (97.5%).
conclusionCompared to array data imputed into 1000 Genomes, mid-pass performed better across all metrics and identified novel population-specific variants with potential disease relevance. We hope our work will reduce financial barriers for geneticists from underrepresented populations to characterize their genomes prior to biomedical genetic applications.
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Registered trials
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.