Literature DB >> 16137993

Power and sample size calculations for genetic case/control studies using gene-centric SNP maps: application to human chromosomes 6, 21, and 22 in three populations.

Francisco M De La Vega1, Derek Gordon, Xiaoping Su, Charles Scafe, Hadar Isaac, Dennis A Gilbert, Eugene G Spier.   

Abstract

Power and sample size calculations are critical parts of any research design for genetic association. We present a method that utilizes haplotype frequency information and average marker-marker linkage disequilibrium on SNPs typed in and around all genes on a chromosome. The test statistic used is the classic likelihood ratio test applied to haplotypes in case/control populations. Haplotype frequencies are computed through specification of genetic model parameters. Power is determined by computation of the test's non-centrality parameter. Power per gene is computed as a weighted average of the power assuming each haplotype is associated with the trait. We apply our method to genotype data from dense SNP maps across three entire chromosomes (6, 21, and 22) for three different human populations (African-American, Caucasian, Chinese), three different models of disease (additive, dominant, and multiplicative) and two trait allele frequencies (rare, common). We perform a regression analysis using these factors, average marker-marker disequilibrium, and the haplotype diversity across the gene region to determine which factors most significantly affect average power for a gene in our data. Also, as a 'proof of principle' calculation, we perform power and sample size calculations for all genes within 100 kb of the PSORS1 locus (chromosome 6) for a previously published association study of psoriasis. Results of our regression analysis indicate that four highly significant factors that determine average power to detect association are: disease model, average marker-marker disequilibrium, haplotype diversity, and the trait allele frequency. These findings may have important implications for the design of well-powered candidate gene association studies. Our power and sample size calculations for the PSORS1 gene appear consistent with published findings, namely that there is substantial power (>0.99) for most genes within 100 kb of the PSORS1 locus at the 0.01 significance level. Copyright 2005 S. Karger AG, Basel.

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Year:  2005        PMID: 16137993     DOI: 10.1159/000087918

Source DB:  PubMed          Journal:  Hum Hered        ISSN: 0001-5652            Impact factor:   0.444


  8 in total

1.  Power and sample size calculations for SNP association studies with censored time-to-event outcomes.

Authors:  Kouros Owzar; Zhiguo Li; Nancy Cox; Sin-Ho Jung
Journal:  Genet Epidemiol       Date:  2012-06-08       Impact factor: 2.135

2.  Promoter polymorphism -119C/G in MYG1 (C12orf10) gene is related to vitiligo susceptibility and Arg4Gln affects mitochondrial entrance of Myg1.

Authors:  Mari-Anne Philips; Külli Kingo; Maire Karelson; Ranno Rätsep; Eerik Aunin; Ene Reimann; Paula Reemann; Orm Porosaar; Jonas Vikeså; Finn C Nielsen; Eero Vasar; Helgi Silm; Sulev Kõks
Journal:  BMC Med Genet       Date:  2010-04-08       Impact factor: 2.103

3.  FTO gene polymorphisms and obesity risk: a meta-analysis.

Authors:  Sihua Peng; Yimin Zhu; Fangying Xu; Xiaobin Ren; Xiaobo Li; Maode Lai
Journal:  BMC Med       Date:  2011-06-08       Impact factor: 8.775

4.  A detailed Hapmap of the Sitosterolemia locus spanning 69 kb; differences between Caucasians and African-Americans.

Authors:  Bhaswati Pandit; Gwang-Sook Ahn; Starr E Hazard; Derek Gordon; Shailendra B Patel
Journal:  BMC Med Genet       Date:  2006-02-28       Impact factor: 2.103

5.  SUP: an extension to SLINK to allow a larger number of marker loci to be simulated in pedigrees conditional on trait values.

Authors:  Mathieu Lemire
Journal:  BMC Genet       Date:  2006-07-03       Impact factor: 2.797

6.  Are molecular haplotypes worth the time and expense? A cost-effective method for applying molecular haplotypes.

Authors:  Mark A Levenstien; Jürg Ott; Derek Gordon
Journal:  PLoS Genet       Date:  2006-06-28       Impact factor: 5.917

7.  Testing for linkage and association across the dihydrolipoyl dehydrogenase gene region with Alzheimer's disease in three sample populations.

Authors:  Abraham M Brown; Derek Gordon; Hsinhwa Lee; Fabienne Wavrant-De Vrièze; Elena Cellini; Silvia Bagnoli; Benedetta Nacmias; Sandro Sorbi; John Hardy; John P Blass
Journal:  Neurochem Res       Date:  2007-03-07       Impact factor: 3.996

8.  PGA: power calculator for case-control genetic association analyses.

Authors:  Idan Menashe; Philip S Rosenberg; Bingshu E Chen
Journal:  BMC Genet       Date:  2008-05-13       Impact factor: 2.797

  8 in total

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