Evidence map›Paper›PMID 38014869›Full record

ArticleGenetic epidemiology2024

DYNATE: Localizing rare-variant association regions via multiple testing embedded in an aggregation tree.

Xuechan Li, John Pura, Andrew Allen, Kouros Owzar, Jianfeng Lu, Matthew Harms, Jichun Xie

Abstract read
In one paragraph

Article in Genetic epidemiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
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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

7 authors.

Xuechan LiNovartis Pharmaceuticals Corporation, Basel, Switzerland.
John PuraAstraZeneca, Cambridge, UK.
Andrew AllenDepartment of Biostatistics and Bioinformatics, Duke University, Durham, North Carolina, USA.
Kouros OwzarDepartment of Biostatistics and Bioinformatics, Duke University, Durham, North Carolina, USA.
Jianfeng LuDepartment of Mathematics, Duke University, Durham, North Carolina, USA.
Matthew HarmsDepartment of Neurology, Columbia University, Broadway, New York, USA.
Jichun XieDepartment of Biostatistics and Bioinformatics, Duke University, Durham, North Carolina, USA.ORCID 0000-0001-5905-6728

Funding

New computational methods to dynamically pinpointing the subregions carrying disease-associated rare variantsR01HG012555 · NHGRI · DUKE UNIVERSITY · PI XIE, JICHUN · 2022 to 2025
$1.6M
NHGRI NIH HHS R01 HG012555NIH HHS 1R01HG012555-01
6 · The paper itself

Abstract

Rare-variants (RVs) genetic association studies enable researchers to uncover the variation in phenotypic traits left unexplained by common variation. Traditional single-variant analysis lacks power; thus, researchers have developed various methods to aggregate the effects of RVs across genomic regions to study their collective impact. Some existing methods utilize a static delineation of genomic regions, often resulting in suboptimal effect aggregation, as neutral subregions within the test region will result in an attenuation of signal. Other methods use varying windows to search for signals but often result in long regions containing many neutral RVs. To pinpoint short genomic regions enriched for disease-associated RVs, we developed a novel method, DYNamic Aggregation TEsting (DYNATE). DYNATE dynamically and hierarchically aggregates smaller genomic regions into larger ones and performs multiple testing for disease associations with a controlled weighted false discovery rate. DYNATE's main advantage lies in its strong ability to identify short genomic regions highly enriched for disease-associated RVs. Extensive numerical simulations demonstrate the superior performance of DYNATE under various scenarios compared with existing methods. We applied DYNATE to an amyotrophic lateral sclerosis study and identified a new gene, EPG5, harboring possibly pathogenic mutations.

Indexed as

Genetic VariationTreesAutophagy-Related ProteinsGenetic Association StudiesGenome-Wide Association StudyHumansModels, GeneticMutationVesicular Transport ProteinsAutophagy-Related ProteinsEPG5 protein, humanVesicular Transport Proteinsaggregation treemultiple testingrare-variant associations

Identifiers

PMID38014869
PMCPMC10842871

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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.