Evidence map›Paper›PMID 37067496›Full record

ArticleBioinformatics (Oxford, England)2023

Multivariate genome-wide association analysis by iterative hard thresholding.

Benjamin B Chu, Seyoon Ko, Jin J Zhou, Aubrey Jensen, Hua Zhou, Janet S Sinsheimer, Kenneth Lange

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Bioinformatics (Oxford, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Benjamin B ChuDepartment of Computational Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095-1554, United States.ORCID 0000-0001-8342-2361
Seyoon KoDepartment of Computational Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095-1554, United States.
Jin J ZhouDepartment of Biostatistics, Fielding School of Public Health at UCLA, Los Angeles, CA 90095-1554, United States.
Aubrey JensenDepartment of Biostatistics, Fielding School of Public Health at UCLA, Los Angeles, CA 90095-1554, United States.
Hua ZhouDepartment of Computational Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095-1554, United States.
Janet S SinsheimerDepartment of Computational Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095-1554, United States.
Kenneth LangeDepartment of Computational Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095-1554, United States.ORCID 0000-0002-1313-5030

Funding

Training Grant in Genomic Analysis and InterpretationT32HG002536 · NHGRI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Valerie A Arboleda, Harold Pimentel · 2002 to 2026
$8.6M
Genomics, GPUs, and Next Generation Computational StatisticsR01HG006139 · NHGRI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI SOBEL, ERIC · 2011 to 2023
$5.1M
Modeling, Inference, and Optimization for Genomic and Biomedical Big DataR35GM141798 · NIGMS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI LANGE, KENNETH L · 2021 to 2025
$2.7M
Integrative approaches for mapping the genetic risk of complex traitsR01HG009120 · NHGRI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI PASANIUC, BOGDAN · 2017 to 2021
$2.3M
Develop T2D Patient-Centered Treatment Suggestion Rule using EMR dataK01DK106116 · NIDDK · UNIVERSITY OF ARIZONA · PI ZHOU, JIN · 2016 to 2019
$524k
A Role for Glycemic Variation in Optimizing Management of Diabetes and Vascular ComplicationsR21HL150374 · NHLBI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI REAVEN, PETER D, ZHOU, JIN · 2020 to 2021
$250k
NHGRI NIH HHS R01 HG006139NHGRI NIH HHS R01 HG009120NHGRI NIH HHS T32 HG002536NHLBI NIH HHS R21 HL150374NIDDK NIH HHS K01 DK106116NIGMS NIH HHS R35 GM141798NIH HHS T32-HG02536
6 · The paper itself

Abstract

motivationIn a genome-wide association study, analyzing multiple correlated traits simultaneously is potentially superior to analyzing the traits one by one. Standard methods for multivariate genome-wide association study operate marker-by-marker and are computationally intensive.

resultsWe present a sparsity constrained regression algorithm for multivariate genome-wide association study based on iterative hard thresholding and implement it in a convenient Julia package MendelIHT.jl. In simulation studies with up to 100 quantitative traits, iterative hard thresholding exhibits similar true positive rates, smaller false positive rates, and faster execution times than GEMMA's linear mixed models and mv-PLINK's canonical correlation analysis. On UK Biobank data with 470 228 variants, MendelIHT completed a three-trait joint analysis (n=185 656) in 20 h and an 18-trait joint analysis (n=104 264) in 53 h with an 80 GB memory footprint. In short, MendelIHT enables geneticists to fit a single regression model that simultaneously considers the effect of all SNPs and dozens of traits. AVAILABILITY AND IMPLEMENTATION: Software, documentation, and scripts to reproduce our results are available from https://github.com/OpenMendel/MendelIHT.jl.

Indexed as

Genome-Wide Association StudySoftwareAlgorithmsComputer SimulationPhenotypePolymorphism, Single Nucleotide

Identifiers

PMID37067496
PMCPMC10133532

What OpenQuestion 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 OpenQuestion graph.