Evidence map›Paper›PMID 33536225›Full record

ArticleGenome research2021

Low-pass sequencing increases the power of GWAS and decreases measurement error of polygenic risk scores compared to genotyping arrays.

Jeremiah H Li, Chase A Mazur, Tomaz Berisa, Joseph K Pickrell

Abstract read
In one paragraph

Article in Genome research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 75 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
75citing papers in PubMed, 1 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

75 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  13. Sequencing and health data resource of children of African ancestry.Genetics in medicine : official journal of the American College of Medical Genetics · 2026
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  20. Low-coverage whole-genome sequencing facilitates accurate and cost-effective haplotype reconstruction in complex mouse crosses.Mammalian genome : official journal of the International Mammalian Genome Society · 2025
    Article

15 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

4 authors.

Jeremiah H LiGencove, Incorporated, New York, New York 10016, USA.
Chase A MazurGencove, Incorporated, New York, New York 10016, USA.
Tomaz BerisaGencove, Incorporated, New York, New York 10016, USA.
Joseph K PickrellGencove, Incorporated, New York, New York 10016, USA.

Funding

Scalable and accurate polygenic risk profiling with low-pass whole genome sequencingR43HG010596 · NHGRI · GENCOVE, INC. · PI PICKRELL, JOSEPH · 2019 to 2019
$330k
NHGRI NIH HHS R43 HG010596
6 · The paper itself

Abstract

Low-pass sequencing (sequencing a genome to an average depth less than 1× coverage) combined with genotype imputation has been proposed as an alternative to genotyping arrays for trait mapping and calculation of polygenic scores. To empirically assess the relative performance of these technologies for different applications, we performed low-pass sequencing (targeting coverage levels of 0.5× and 1×) and array genotyping (using the Illumina Global Screening Array [GSA]) on 120 DNA samples derived from African- and European-ancestry individuals that are part of the 1000 Genomes Project. We then imputed both the sequencing data and the genotyping array data to the 1000 Genomes Phase 3 haplotype reference panel using a leave-one-out design. We evaluated overall imputation accuracy from these different assays as well as overall power for GWAS from imputed data and computed polygenic risk scores for coronary artery disease and breast cancer using previously derived weights. We conclude that low-pass sequencing plus imputation, in addition to providing a substantial increase in statistical power for genome-wide association studies, provides increased accuracy for polygenic risk prediction at effective coverages of ∼0.5× and higher compared to the Illumina GSA.

Indexed as

Genome-Wide Association StudyGenotypeHigh-Throughput Nucleotide SequencingGenome, HumanHaplotypesHumansRisk Factors

Identifiers

PMID33536225
PMCPMC8015847

What OpenQuestion holds

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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 OpenQuestion graph.