Evidence map›Paper›PMID 22319458›Full record

ArticlePLoS genetics2012

The empirical power of rare variant association methods: results from sanger sequencing in 1,998 individuals.

Martin Ladouceur, Zari Dastani, Yurii S Aulchenko, Celia M T Greenwood, J Brent Richards

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In one paragraph

Article in PLoS genetics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 75 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
75citing papers in PubMed, 2 pooled it
–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

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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

75 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  19. Phenotypic extremes in rare variant study designs.European journal of human genetics : EJHG · 2016
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15 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Martin LadouceurDepartment of Human Genetics, McGill University, Montreal, Canada.
Zari Dastani
Yurii S Aulchenko
Celia M T Greenwood
J Brent Richards

Funding

Canadian Institutes of Health Research
6 · The paper itself

Abstract

The role of rare genetic variation in the etiology of complex disease remains unclear. However, the development of next-generation sequencing technologies offers the experimental opportunity to address this question. Several novel statistical methodologies have been recently proposed to assess the contribution of rare variation to complex disease etiology. Nevertheless, no empirical estimates comparing their relative power are available. We therefore assessed the parameters that influence their statistical power in 1,998 individuals Sanger-sequenced at seven genes by modeling different distributions of effect, proportions of causal variants, and direction of the associations (deleterious, protective, or both) in simulated continuous trait and case/control phenotypes. Our results demonstrate that the power of recently proposed statistical methods depend strongly on the underlying hypotheses concerning the relationship of phenotypes with each of these three factors. No method demonstrates consistently acceptable power despite this large sample size, and the performance of each method depends upon the underlying assumption of the relationship between rare variants and complex traits. Sensitivity analyses are therefore recommended to compare the stability of the results arising from different methods, and promising results should be replicated using the same method in an independent sample. These findings provide guidance in the analysis and interpretation of the role of rare base-pair variation in the etiology of complex traits and diseases.

Indexed as

Genetic Predisposition to DiseaseGenetic VariationModels, Statistical1-Alkyl-2-acetylglycerophosphocholine EsteraseComputer SimulationData Interpretation, StatisticalGenetic Association StudiesGenome, HumanHumansPhenotypePhospholipases A2Sample SizeSequence Analysis, DNA1-Alkyl-2-acetylglycerophosphocholine EsterasePhospholipases A2PLA2G7 protein, human

Identifiers

PMID22319458
PMCPMC3271058

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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.