Evidence map›Paper›PMID 37873337›Full record

ArticlemedRxiv : the preprint server for health sciences2023

Integration of Expression QTLs with fine mapping via SuSiE.

Xiangyu Zhang, Wei Jiang, Hongyu Zhao

Open access · greenAbstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Xiangyu ZhangDepartment of Biostatistics, School of Public Health, Yale University, New Haven, Connecticut, United States of America.
Wei JiangDepartment of Biostatistics, School of Public Health, Yale University, New Haven, Connecticut, United States of America.
Hongyu ZhaoDepartment of Biostatistics, School of Public Health, Yale University, New Haven, Connecticut, United States of America.
Yale University · US

Funding

Laboratory, Data Analysis, and Coordinating Center (LDACC) for the Developmental Human Genotype-Tissue Expression ProjectU24HG012108 · NHGRI · YALE UNIVERSITY · PI GERSTEIN, MARK BENDER, HUTTNER, ANITA JULIANE · 2021 to 2025
$8.7M
Novel statistical methods and tools to integrate multiple endophenotypes and functional annotation data to study the roles of rare variants in complex human diseases using sequencing dataR01GM134005 · NIGMS · YALE UNIVERSITY · PI WU, BAOLIN, ZHAO, HONGYU · 2020 to 2023
$1.6M
NHGRI NIH HHS U24 HG012108NIGMS NIH HHS R01 GM134005
6 · The paper itself

Abstract

Genome-wide association studies (GWASs) have achieved remarkable success in associating thousands of genetic variants with complex traits. However, the presence of linkage disequilibrium (LD) makes it challenging to identify the causal variants. To address this critical gap from association to causation, many fine mapping methods have been proposed to assign well-calibrated probabilities of causality to candidate variants, taking into account the underlying LD pattern. In this manuscript, we introduce a statistical framework that incorporates expression quantitative trait locus (eQTL) information to fine mapping, built on the sum of single-effects (SuSiE) regression model. Our new method, SuSiE

Identifiers

PMID37873337
PMCPMC10593033
OpenAlexW4387338431

What OpenQuestion holds

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LicenceCC BY
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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.