Evidence map›Paper›PMID 27039378›Full record

ArticleGenome biology2016

Multiple testing correction in linear mixed models.

Jong Wha J Joo, Farhad Hormozdiari, Buhm Han, Eleazar Eskin

Abstract read
In one paragraph

Article in Genome biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed, 3 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

37 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
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  8. FlexLMM: a Nextflow linear mixed model framework for GWAS.Bioinformatics (Oxford, England) · 2024
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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

4 authors.

Jong Wha J JooBioinformatics IDP, University of California, Los Angeles, CA, USA.
Farhad HormozdiariComputer Science Department, University of California, Los Angeles, CA, USA.
Buhm HanDepartment of Convergence Medicine, University of Ulsan College of Medicine & Asan Institute for Life Sciences, Asan Medical Center, Seoul, 138-736, Republic of Korea. buhm.han@amc.seoul.kr.
Eleazar EskinComputer Science Department, University of California, Los Angeles, CA, USA. eeskin@cs.ucla.edu.

Funding

ULTRASTRUCTURE OF THE INTIMA IN EARLY LESION FORMATIONP01HL030568 · NHLBI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI FOGELMAN, ALAN M · 1985 to 2019
$55.2M
Systems genomics of metabolic syndrome traitsP01HL028481 · NHLBI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI LUSIS, ALDONS JAKE · 1985 to 2019
$50.2M
Substance Abuse & Behavioral Disinhibition: Integrating Genes & EnvironmentU01DA024417 · NIDA · UNIVERSITY OF MINNESOTA · PI IACONO, WILLIAM G. · 2007 to 2010
$10.8M
Training U54EB020403 · NIBIB · UNIVERSITY OF SOUTHERN CALIFORNIA · PI THOMPSON, PAUL M · 2014 to 2018
$10.1M
Integrative Center for Neurogenetics and Neurogenomics - OverallP30NS062691 · NINDS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI COPPOLA, GIOVANNI · 2009 to 2018
$7.4M
INTEGRATIVE GENETIC APPROACHES TO GENE-AIR POLLUTION INTERACTIONS IN ASTHMAR01ES021801 · NIEHS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI AKBARI, OMID, ALLAYEE, HOOMAN · 2012 to 2016
$3.9M
An integrated molecular approach to understand variation in iron metabolismR01GM083198 · NIGMS · UNIVERSITY OF FLORIDA · PI VULPE, CHRISTOPHER D · 2012 to 2015
$2.7M
Genetic Regulation of Gene Expression and its Impact on Phenotypes - SupplementR01MH101782 · NIMH · STANFORD UNIVERSITY · PI SABATTI, CHIARA · 2013 to 2016
$1.3M
Correcting for Population Structure in Gene-by-Environment Interaction StudiesR01ES022282 · NIEHS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI ESKIN, ELEAZAR · 2013 to 2015
$1.2M
Discovering the Genetic Basis of HypertensionK25HL080079 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI ESKIN, ELEAZAR · 2006 to 2010
$685k
NHLBI NIH HHS K25 HL080079NHLBI NIH HHS K25-HL080079NHLBI NIH HHS P01 HL028481NHLBI NIH HHS P01 HL030568NHLBI NIH HHS P01-HL28481NHLBI NIH HHS P01-HL30568NIBIB NIH HHS U54 EB020403NIBIB NIH HHS U54EB020403NIDA NIH HHS U01 DA024417NIDA NIH HHS U01-DA024417NIEHS NIH HHS R01 ES021801NIEHS NIH HHS R01-ES021801NIEHS NIH HHS R01 ES022282NIEHS NIH HHS R01-ES022282NIGMS NIH HHS R01 GM083198NIGMS NIH HHS R01-GM083198NIMH NIH HHS R01 MH101782NIMH NIH HHS R01-MH101782NINDS NIH HHS P30 NS062691
6 · The paper itself

Abstract

backgroundMultiple hypothesis testing is a major issue in genome-wide association studies (GWAS), which often analyze millions of markers. The permutation test is considered to be the gold standard in multiple testing correction as it accurately takes into account the correlation structure of the genome. Recently, the linear mixed model (LMM) has become the standard practice in GWAS, addressing issues of population structure and insufficient power. However, none of the current multiple testing approaches are applicable to LMM.

resultsWe were able to estimate per-marker thresholds as accurately as the gold standard approach in real and simulated datasets, while reducing the time required from months to hours. We applied our approach to mouse, yeast, and human datasets to demonstrate the accuracy and efficiency of our approach.

conclusionsWe provide an efficient and accurate multiple testing correction approach for linear mixed models. We further provide an intuition about the relationships between per-marker threshold, genetic relatedness, and heritability, based on our observations in real data.

Indexed as

AnimalsComputational BiologyDatabases, GeneticGenome-Wide Association StudyHumansLinear ModelsMiceSoftwareYeasts

Identifiers

PMID27039378
PMCPMC4818520

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.