Evidence map›Paper›PMID 23964661›Full record

ArticleBMC genomics2013

Combined genotype and haplotype tests for region-based association studies.

Sergii Zakharov, Tien Yin Wong, Tin Aung, Eranga Nishanthie Vithana, Chiea Chuen Khor, Agus Salim, Anbupalam Thalamuthu

Abstract read
In one paragraph

Article in BMC genomics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Sergii ZakharovHuman Genetics, Genome Institute of Singapore, Singapore, Singapore. zakharovs99@gis.a-star.edu.sg.
Tien Yin Wong
Tin Aung
Eranga Nishanthie Vithana
Chiea Chuen Khor
Agus Salim
Anbupalam Thalamuthu

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAlthough single-SNP analysis has proven to be useful in identifying many disease-associated loci, region-based analysis has several advantages. Empirically, it has been shown that region-based genotype and haplotype approaches may possess much higher power than single-SNP statistical tests. Both high quality haplotypes and genotypes may be available for analysis given the development of next generation sequencing technologies and haplotype assembly algorithms.

resultsAs generally it is unknown whether genotypes or haplotypes are more relevant for identifying an association, we propose to use both of them with the purpose of preserving high power under both genotype and haplotype disease scenarios. We suggest two approaches for a combined association test and investigate the performance of these two approaches based on a theoretical model, population genetics simulations and analysis of a real data set.

conclusionsBased on a theoretical model, population genetics simulations and analysis of a central corneal thickness (CCT) Genome Wide Association Study (GWAS) data set we have shown that combined genotype and haplotype approach has a high potential utility for applications in association studies.

Indexed as

HaplotypesAlgorithmsComputer SimulationData Interpretation, StatisticalGenetic Predisposition to DiseaseGenetics, PopulationGenome-Wide Association StudyGenotyping TechniquesHumansLinkage DisequilibriumModels, GeneticModels, StatisticalPolymorphism, Single Nucleotide

Identifiers

PMID23964661
PMCPMC3852120

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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.