Evidence map›Paper›PMID 34686674›Full record

ArticleNature communications2021

The flashfm approach for fine-mapping multiple quantitative traits.

N Hernández, J Soenksen, P Newcombe, M Sandhu, I Barroso, C Wallace, J L Asimit

Abstract read
In one paragraph

Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

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

  1. Pooled it
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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.

N HernándezMRC Biostatistics Unit, University of Cambridge, Cambridge, UK.ORCID 0000-0002-0710-5652
J SoenksenExeter Centre of Excellence for Diabetes Research (EXCEED), University of Exeter Medical School, Exeter, UK.ORCID 0000-0002-4361-4200
P NewcombeMRC Biostatistics Unit, University of Cambridge, Cambridge, UK.
M SandhuDept of Epidemiology & Biostatistics, School of Public Health, Imperial College London, London, UK.
I BarrosoExeter Centre of Excellence for Diabetes Research (EXCEED), University of Exeter Medical School, Exeter, UK.ORCID 0000-0001-5800-4520
C WallaceMRC Biostatistics Unit, University of Cambridge, Cambridge, UK.ORCID 0000-0001-9755-1703
J L AsimitMRC Biostatistics Unit, University of Cambridge, Cambridge, UK. jennifer.asimit@mrc-bsu.cam.ac.uk.ORCID 0000-0002-4857-2249

Funding

Medical Research Council MC_UU_00002/4Medical Research Council MC UU 00002/9Medical Research Council MC_UU_00002/9Medical Research Council MR/R021368/1Medical Research Council MR/S019669/1Wellcome Trust
6 · The paper itself

Abstract

Joint fine-mapping that leverages information between quantitative traits could improve accuracy and resolution over single-trait fine-mapping. Using summary statistics, flashfm (flexible and shared information fine-mapping) fine-maps signals for multiple traits, allowing for missing trait measurements and use of related individuals. In a Bayesian framework, prior model probabilities are formulated to favour model combinations that share causal variants to capitalise on information between traits. Simulation studies demonstrate that both approaches produce broadly equivalent results when traits have no shared causal variants. When traits share at least one causal variant, flashfm reduces the number of potential causal variants by 30% compared with single-trait fine-mapping. In a Ugandan cohort with 33 cardiometabolic traits, flashfm gave a 20% reduction in the total number of potential causal variants from single-trait fine-mapping. Here we show flashfm is computationally efficient and can easily be deployed across publicly available summary statistics for signals in up to six traits.

Indexed as

Bayes TheoremChromosome MappingComputer SimulationGenome, HumanGenome-Wide Association StudyHumansLinkage DisequilibriumModels, GeneticPhenotypePolymorphism, Single NucleotideQuantitative Trait Loci

Identifiers

PMID34686674
PMCPMC8536717

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.