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Title: Imprinting Test of Disease-associated SNPs under Mixture Model
Originating Office: IAS
Speaker: Guo, Jianhua
Issue Date: 19-Dec-2013
Event Date: 19-Dec-2013
Group/Series/Folder: Record Group 8.15 - Institute for Advanced Study
Series 3 - Audio-visual Materials
Location: 8.15:3 EF
Notes: HKUST International Forum on Probability and Statistics. Talk no. 6.
Title from opening screen.
The Second HKUST International Forum on Probability and Statistics (2013), held 19 December, 2013, at the Hong Kong University of Science and Technology. Co-sponsored by the HKUST Jockey Club Institute for Advanced Study and the Center for Statistical Science.
Abstract: Genomic imprinting represents a known aspect of the etiology of schizophrenia, a serious and common neuropsychiatric disease. This study delineates the role of imprinting in the relationships between schizophrenia-associated single nucleotide polymorphisms (SNPs) of the GABRB2 gene for its beta2 subunit of GABAA receptors and the quantitative trait of GABRB2 mRNA expression. The imprinting phenomenon depicts differential expression levels of the allele depending on its parental origin. When the parental origin is unknown, the expression level has a finite normal mixture distribution. In such application, a random sample on expression levels consists of three subsamples according to the number of minor alleles an individual possesses, one of which is the mixture and the rest two are homogeneous. This understanding leads to a likelihood ratio test (LRT) for the presence of the imprinting. Due to non-regularity of the finite mixture model, the classical asymptotic conclusions on likelihood-based inferences are inapplicable. The talk shows that the maximum likelihood estimator of the mixing distribution remains consistent. More interestingly, helped by homogeneous subsamples, the LRT statistic has an elegant and rather distinct mixture chi-squared null limiting distribution. Simulation studies confirm that the limiting distribution provides precise approximations to the finite sample distributions in various parameter settings. The LRT is applied to expression data sets on the schizophrenia susceptibility gene GABRB2. Our analyses provide evidences of imprintings on a number of isoform expressions of its GABAA receptor beta2 subunit protein encoded by the GABRB2 gene.
Duration: 33 min.
Appears in Series:8.15:3 - Audio-visual Materials
Videos for Public -- Distinguished Lectures