Evidence map›Paper›PMID 21104888›Full record

ArticleGenetic epidemiology2010

A simple and fast two-locus quality control test to detect false positives due to batch effects in genome-wide association studies.

Sang Hong Lee, Dale R Nyholt, Stuart Macgregor, Anjali K Henders, Krina T Zondervan, Grant W Montgomery, Peter M Visscher

Abstract read
In one paragraph

Article in Genetic epidemiology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 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

7 authors.

Sang Hong LeeQueensland Institute of Medical Research, Herston, Queensland, Australia. hong.lee@qimr.edu.au
Dale R Nyholt
Stuart Macgregor
Anjali K Henders
Krina T Zondervan
Grant W Montgomery
Peter M Visscher

Funding

Wellcome Trust 076113Wellcome Trust 084766Wellcome Trust 085235
6 · The paper itself

Abstract

The impact of erroneous genotypes having passed standard quality control (QC) can be severe in genome-wide association studies, genotype imputation, and estimation of heritability and prediction of genetic risk based on single nucleotide polymorphisms (SNP). To detect such genotyping errors, a simple two-locus QC method, based on the difference in test statistic of association between single SNPs and pairs of SNPs, was developed and applied. The proposed approach could detect many problematic SNPs with statistical significance even when standard single SNP QC analyses fail to detect them in real data. Depending on the data set used, the number of erroneous SNPs that were not filtered out by standard single SNP QC but detected by the proposed approach varied from a few hundred to thousands. Using simulated data, it was shown that the proposed method was powerful and performed better than other tested existing methods. The power of the proposed approach to detect erroneous genotypes was ∼80% for a 3% error rate per SNP. This novel QC approach is easy to implement and computationally efficient, and can lead to a better quality of genotypes for subsequent genotype-phenotype investigations.

Indexed as

Genetic LociQuality ControlGenome, HumanGenome-Wide Association StudyGenotypeHumansModels, GeneticPolymorphism, Single Nucleotide

Identifiers

PMID21104888
PMCPMC3674525

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.