Evidence map›Paper›PMID 22363405›Full record

ArticlePloS one2012

Sample reproducibility of genetic association using different multimarker TDTs in genome-wide association studies: characterization and a new approach.

Mara M Abad-Grau, Nuria Medina-Medina, Rosana Montes-Soldado, Fuencisla Matesanz, Vineet Bafna

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In one paragraph

Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Current strategies for mutation detection in phenotype-driven screens utilising next generation sequencing.Mammalian genome : official journal of the International Mammalian Genome Society · 2015
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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

5 authors.

Mara M Abad-GrauDepartamento de Lenguajes y Sistemas Informáticos, ETS Ingeniera Informática y de Telecomunicaciones-CITIC, Universidad de Granada, Granada, Spain. mabad@ugr.es
Nuria Medina-Medina
Rosana Montes-Soldado
Fuencisla Matesanz
Vineet Bafna

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Multimarker Transmission/Disequilibrium Tests (TDTs) are very robust association tests to population admixture and structure which may be used to identify susceptibility loci in genome-wide association studies. Multimarker TDTs using several markers may increase power by capturing high-degree associations. However, there is also a risk of spurious associations and power reduction due to the increase in degrees of freedom. In this study we show that associations found by tests built on simple null hypotheses are highly reproducible in a second independent data set regardless the number of markers. As a test exhibiting this feature to its maximum, we introduce the multimarker 2-Groups TDT (mTDT(2G)), a test which under the hypothesis of no linkage, asymptotically follows a χ2 distribution with 1 degree of freedom regardless the number of markers. The statistic requires the division of parental haplotypes into two groups: disease susceptibility and disease protective haplotype groups. We assessed the test behavior by performing an extensive simulation study as well as a real-data study using several data sets of two complex diseases. We show that mTDT(2G) test is highly efficient and it achieves the highest power among all the tests used, even when the null hypothesis is tested in a second independent data set. Therefore, mTDT(2G) turns out to be a very promising multimarker TDT to perform genome-wide searches for disease susceptibility loci that may be used as a preprocessing step in the construction of more accurate genetic models to predict individual susceptibility to complex diseases.

Indexed as

Computer SimulationCrohn DiseaseDatabases, GeneticFamilyGenetic MarkersGenetics, PopulationGenome-Wide Association StudyGenotypeHaplotypesHumansLinkage DisequilibriumMultiple SclerosisParentsReproducibility of ResultsGenetic Markers

Identifiers

PMID22363405
PMCPMC3281822

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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.