An Entropy-Based Statistic for Genomewide Association Studies
AUTOR(ES)
Zhao, Jinying
FONTE
American Society of Human Genetics
RESUMO
Efficient genotyping methods and the availability of a large collection of single-nucleotide polymorphisms provide valuable tools for genetic studies of human disease. The standard χ2 statistic for case-control studies, which uses a linear function of allele frequencies, has limited power when the number of marker loci is large. We introduce a novel test statistic for genetic association studies that uses Shannon entropy and a nonlinear function of allele frequencies to amplify the differences in allele and haplotype frequencies to maintain statistical power with large numbers of marker loci. We investigate the relationship between the entropy-based test statistic and the standard χ2 statistic and show that, in most cases, the power of the entropy-based statistic is greater than that of the standard χ2 statistic. The distribution of the entropy-based statistic and the type I error rates are validated using simulation studies. Finally, we apply the new entropy-based test statistic to two real data sets, one for the COMT gene and schizophrenia and one for the MMP-2 gene and esophageal carcinoma, to evaluate the performance of the new method for genetic association studies. The results show that the entropy-based statistic obtained smaller P values than did the standard χ2 statistic.
ACESSO AO ARTIGO
http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=1226192Documentos Relacionados
- Nonparametric Entropy-Based Tests of Independence Between Stochastic Processes
- Entropy-based gene ranking without selection bias for the predictive classification of microarray data
- Um novo algoritmo baseado em entropia para filtragem da interferÃncia frente-verso
- GenomicLand: Software for genome-wide association studies and genomic prediction
- Genome-wide association studies in Alzheimer's disease