Evidence map›Paper›PMID 16451586›Full record

ArticleBMC genetics2005

A genome-wide linkage and association study using COGA data.

Xiaofeng Zhu, Richard Cooper, Donghui Kan, Guichan Cao, Xiaodong Wu

Abstract read
In one paragraph

Article in BMC genetics, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Recent advances in genetic studies of alcohol use disorders.Current genetic medicine reports · 2020
    Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Statistical Analysis in Genetic Studies of Mental Illnesses.Statistical science : a review journal of the Institute of Mathematical Statistics · 2011
    Article
  8. An Association Test for Multiple Traits Based on the Generalized Kendall's Tau.Journal of the American Statistical Association · 2010
    Article
  9. Article
  10. Article
  11. 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

5 authors.

Xiaofeng ZhuDepartment of Preventive Medicine and Epidemiology, Loyola University Medical Center, Maywood, IL 60153, USA. xzhu1@lumc.edu
Richard Cooper
Donghui Kan
Guichan Cao
Xiaodong Wu

Funding

Defining an Obesity QTL on Chromosome 3qR01HL074166 · NHLBI · LOYOLA UNIVERSITY CHICAGO · PI ZHU, XIAOFENG · 2004 to 2007
$2.9M
NHLBI NIH HHS HL74166NHLBI NIH HHS R01 HL074166
6 · The paper itself

Abstract

backgroundGenome-wide association will soon be available to use as an adjunct to traditional linkage analysis. We studied alcoholism in 119 families collected by the Collaborative Study on the Genetics of Alcoholism and made available in Genetic Analysis Workshop 14, using genome-wide linkage and association analyses.

methodsGenome-wide linkage analysis was first performed using microsatellite markers and a region with the strongest linkage evidence was further analyzed using single-nucleotide polymorphisms (SNPs). Family based genome-wide association test was also conducted using the SNPs.

resultsNonparametric linkage analysis revealed weak linkage evidence on chromosome 7, and association analysis identified SNP tsc0515272 on chromosome 3 as significantly associated with alcoholism.

conclusionLinkage analysis may require large sample sizes and high quality genotyping and marker maps to adequately improve power, while association analysis could hold more promise in efforts to identify variants responsible for complex traits.

Indexed as

Cooperative BehaviorDatabases, GeneticGenetic LinkageGenome-Wide Association StudyAlcoholismFamilyHumansLod ScoreMicrosatellite RepeatsPolymorphism, Single NucleotideStatistics, Nonparametric

Identifiers

PMID16451586
PMCPMC1866809

What OpenQuestion holds

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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.