Evidence map›Paper›PMID 17894890›Full record

ArticleBMC genetics2007

A multi-marker test based on family data in genome-wide association study.

Zhaogong Zhang, Shuanglin Zhang, Qiuying Sha

Abstract read
In one paragraph

Article in BMC genetics, 2007. 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

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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.

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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

3 authors.

Zhaogong ZhangDepartment of Mathematical Sciences, Michigan Technological University, Houghton, MI 49931, USA. zhaogong@mtu.edu
Shuanglin Zhang
Qiuying Sha

Funding

Statistical methods for analyzing high-throughput genotype dataR01HG003054 · NHGRI · LOYOLA UNIVERSITY CHICAGO · PI ZHU, XIAOFENG · 2005 to 2017
$3.6M
Statistical Methods for Mapping Complex Disease GenesR01GM069940 · NIGMS · MICHIGAN TECHNOLOGICAL UNIVERSITY · PI ZHANG, SHUANGLIN · 2005 to 2007
$682k
Statistical Methods for Admixture MappingR03HG003613 · NHGRI · MICHIGAN TECHNOLOGICAL UNIVERSITY · PI ZHANG, SHUANGLIN · 2005 to 2007
$223k
Mapping Complex Disease Genes Incorporating Age-at-onsetR03AG024491 · NIA · MICHIGAN TECHNOLOGICAL UNIVERSITY · PI CHEN, HUANN-SHENG · 2004 to 2005
$142k
NHGRI NIH HHS R03 HG 003613
6 · The paper itself

Abstract

backgroundComplex diseases are believed to be the results of many genes and environmental factors. Hence, multi-marker methods that can use the information of markers from different genes are appropriate for mapping complex disease genes. There already have been several multi-marker methods proposed for case-control studies. In this article, we propose a multi-marker test called a Multi-marker Pedigree Disequilibrium Test (MPDT) to analyze family data from genome-wide association studies. If the parental phenotypes are available, we also propose a two-stage test in which a genomic screening test is used to select SNPs, and then the MPDT is used to test the association of the selected SNPs.

resultsWe use simulation studies to evaluate the performance of the MPDT and the two-stage approach. The results show that the MPDT constantly outperforms the single marker transmission/disequilibrium test (TDT) 1. Comparing the power of the two-stage approach with that of the one-stage approach, which approach is more powerful depends on the value of the prevalence; when the prevalence is no less than 10%, the two-stage approach may be more powerful than the one-stage approach. Otherwise, the one-stage approach is more powerful.

conclusionThe proposed MPDT, is more powerful than the single marker TDT. When the parental phenotypes are available and the prevalence is no less than 10%, the proposed two-stage approach is more powerful than the one-stage approach.

Indexed as

Genome, HumanModels, GeneticAlgorithmsGenetic MarkersGenetic Predisposition to DiseaseGenotypeHumansLinkage DisequilibriumPedigreePhenotypeGenetic Markers

Identifiers

PMID17894890
PMCPMC2121104

What OpenQuestion holds

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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.