Evidence map›Paper›PMID 30263053›Full record

ArticleBMC proceedings2018

Genome-wide association study for multiple phenotype analysis.

Xuan Deng, Biqi Wang, Virginia Fisher, Gina Peloso, Adrienne Cupples, Ching-Ti Liu

Abstract read
In one paragraph

Article in BMC proceedings, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. GWAS for main effects and epistatic interactions for grain morphology traits in wheat.Physiology and molecular biology of plants : an international journal of functional plant biology · 2022
    Article
  3. Article
  4. 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

6 authors.

Xuan DengDepartment of Biostatistics, School of Public Health, Boston University, 801 Massachusetts Avenue 3rd Floor, Boston, MA 02118 USA.
Biqi WangDepartment of Biostatistics, School of Public Health, Boston University, 801 Massachusetts Avenue 3rd Floor, Boston, MA 02118 USA.
Virginia FisherDepartment of Biostatistics, School of Public Health, Boston University, 801 Massachusetts Avenue 3rd Floor, Boston, MA 02118 USA.
Gina PelosoDepartment of Biostatistics, School of Public Health, Boston University, 801 Massachusetts Avenue 3rd Floor, Boston, MA 02118 USA.
Adrienne CupplesDepartment of Biostatistics, School of Public Health, Boston University, 801 Massachusetts Avenue 3rd Floor, Boston, MA 02118 USA.
Ching-Ti LiuDepartment of Biostatistics, School of Public Health, Boston University, 801 Massachusetts Avenue 3rd Floor, Boston, MA 02118 USA.

Funding

Genetic and Environmental Determinants of TriglyceridesU01HL072524 · NHLBI · UNIVERSITY OF MINNESOTA TWIN CITIES · PI ARNETT, DONNA K · 2002 to 2008
$11.9M
GENETIC ANALYSIS OF COMMON DISEASES: AN EVALUATIONR01GM031575 · NIGMS · UNIVERSITY OF TEXAS RIO GRANDE VALLEY · PI ALMASY, LAURA A. · 1985 to 2016
$7.8M
Genomewide Association Study of Lipid Response to Fenofibrate and Dietary FatR01HL091357 · NHLBI · UNIVERSITY OF KENTUCKY · PI ARNETT, DONNA K · 2008 to 2018
$5.8M
NHLBI NIH HHS R01 HL091357NHLBI NIH HHS U01 HL072524NIGMS NIH HHS R01 GM031575
6 · The paper itself

Abstract

Genome-wide association studies often collect multiple phenotypes for complex diseases. Multivariate joint analyses have higher power to detect genetic variants compared with the marginal analysis of each phenotype and are also able to identify loci with pleiotropic effects. We extend the unified score-based association test to incorporate family structure, apply different approaches to analyze multiple traits in GAW20 real samples, and compare the results. Through simulation studies, we confirm that the Type I error rate of the pedigree-based unified score association test is appropriately controlled. In marginalanalysis of triglyceride levels, we found 1 subgenome-wide significant variant on chromosome 6. Joint analyses identified several suggestive genome-wide significant signals, with the pedigree-based unified score association test yielding the greatest number of significant results.

Identifiers

PMID30263053
PMCPMC6156845

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.