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Heterogeneity Model (heterogeneity + model)

Distribution by Scientific Domains

Life Sciences	75%

Selected Abstracts

A polygenic heterogeneity model for common epilepsies with complex genetics

GENES, BRAIN AND BEHAVIOR, Issue 7 2007
L. M. Dibbens
Approximately 40% of epilepsy has a complex genetic basis with an unknown number of susceptibility genes. The effect of each susceptibility gene acting alone is insufficient to account for seizure phenotypes, but certain numbers or combinations of variations in susceptibility genes are predicted to raise the level of neuronal hyperexcitability above a seizure threshold for a given individual in a given environment. Identities of susceptibility genes are beginning to be determined, initially by translation of knowledge gained from gene discovery in the monogenic epilepsies. This entrée into idiopathic epilepsies with complex genetics has led to the experimental validation of susceptibility variants in the first few susceptibility genes. The genetic architecture so far emerging from these results is consistent with what we have designated as a polygenic heterogeneity model for the epilepsies with complex genetics. [source]

Quantitative-trait-locus Mapping in the Presence of Locus Heterogeneity

ANNALS OF HUMAN GENETICS, Issue 6 2006
K Wang
Summary Locus heterogeneity is a concern for quantitative trait locus mapping where phenotypes are likely to be influenced by more than one gene. We introduce a model which generalizes the locus heterogeneity model of Smith (1961) from dichotomous traits to quantitative traits and consider some test statistics for this model. The type I error rates and the power of these statistics are assessed through simulation studies. These statistics are applied to a linkage study of asthma genes. [source]

ESTIMATING THE FALSE NEGATIVE FRACTION FOR A MULTIPLE SCREENING TEST FOR BOWEL CANCER WHEN NEGATIVES ARE NOT VERIFIED

AUSTRALIAN & NEW ZEALAND JOURNAL OF STATISTICS, Issue 4 2004
Chris J. Lloyd
Summary This paper aims to estimate the false negative fraction of a multiple screening test for bowel cancer, where those who give negative results for six consecutive tests do not have their true disease status verified. A subset of these same individuals is given a further screening test, for the sole purpose of evaluating the accuracy of the primary test. This paper proposes a beta heterogeneity model for the probability of a diseased individual ,testing positive' on any single test, and it examines the consequences of this model for inference on the false negative fraction. The method can be generalized to the case where selection for further testing is informative, though this did not appear to be the case for the bowel-cancer data. [source]