ArticlePloS one2008
Computing power and sample size for case-control association studies with copy number polymorphism: application of mixture-based likelihood ratio test.
Article in PloS one, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Estimation of DNA contamination and its sources in genotyped samples.Genetic epidemiology · 2019Article
- Statistical power in genome-wide association studies and quantitative trait locus mapping.Heredity · 2019Article
- Analyzing metabolomics data for association with genotypes using two-component Gaussian mixture distributions.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2018Article
- PRECISION MEDICINE: FROM DIPLOTYPES TO DISPARITIES TOWARDS IMPROVED HEALTH AND THERAPIES.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2018Article
- A novel approach to identify optimal metabotypes of elongase and desaturase activities in prevention of acute coronary syndrome.Metabolomics : Official journal of the Metabolomic Society · 2015Article
- A kernel of truth: statistical advances in polygenic variance component models for complex human pedigrees.Advances in genetics · 2013Article
- ProbABEL package for genome-wide association analysis of imputed data.BMC bioinformatics · 2010Article
- The cost effectiveness of duplicate genotyping for testing genetic association.Annals of human genetics · 2009Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Recent studies suggest that copy number polymorphisms (CNPs) may play an important role in disease susceptibility and onset. Currently, the detection of CNPs mainly depends on microarray technology. For case-control studies, conventionally, subjects are assigned to a specific CNP category based on the continuous quantitative measure produced by microarray experiments, and cases and controls are then compared using a chi-square test of independence. The purpose of this work is to specify the likelihood ratio test statistic (LRTS) for case-control sampling design based on the underlying continuous quantitative measurement, and to assess its power and relative efficiency (as compared to the chi-square test of independence on CNP counts). The sample size and power formulas of both methods are given. For the latter, the CNPs are classified using the Bayesian classification rule. The LRTS is more powerful than this chi-square test for the alternatives considered, especially alternatives in which the at-risk CNP categories have low frequencies. An example of the application of the LRTS is given for a comparison of CNP distributions in individuals of Caucasian or Taiwanese ethnicity, where the LRTS appears to be more powerful than the chi-square test, possibly due to misclassification of the most common CNP category into a less common category.
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