Evidence map›Paper›PMID 20920333›Full record

ArticleBMC genetics2010

Discovering joint associations between disease and gene pairs with a novel similarity test.

Wan-Yu Lin, Wen-Chung Lee

Abstract read
In one paragraph

Article in BMC genetics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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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

3 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

2 authors.

Wan-Yu LinInstitute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, No. 17, Xuzhou Rd., Taipei 100, Taiwan. wlin@uab.edu
Wen-Chung Lee

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGenes in a functional pathway can have complex interactions. A gene might activate or suppress another gene, so it is of interest to test joint associations of gene pairs. To simultaneously detect the joint association between disease and two genes (or two chromosomal regions), we propose a new test with the use of genomic similarities. Our test is designed to detect epistasis in the absence of main effects, main effects in the absence of epistasis, or the presence of both main effects and epistasis.

resultsThe simulation results show that our similarity test with the matching measure is more powerful than the Pearson's χ² test when the disease mutants were introduced at common haplotypes, but is less powerful when the disease mutants were introduced at rare haplotypes. Our similarity tests with the counting measures are more sensitive to marker informativity and linkage disequilibrium patterns, and thus are often inferior to the similarity test with the matching measure and the Pearson's χ² test.

conclusionsIn detecting joint associations between disease and gene pairs, our similarity test is a complementary method to the Pearson's χ² test.

Indexed as

Epistasis, GeneticModels, GeneticDiseaseHaplotypesPolymorphism, Single Nucleotide

Identifiers

PMID20920333
PMCPMC2959050

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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.