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N Rabbee

Publications and source records attributed to N Rabbee.

2 recordsLinked to original sources

A genetic screen for behavioral mutations that perturb dopaminergic homeostasis in mice.

Disruption of dopaminergic (DA) systems is thought to play a central role in the addictive process and in the pathophysiology of schizophrenia. Although inheritance plays an important role in the predisposition to these disorders, the genetic basis of this is not well understood. To provide additional insight, we have performed a modifier screen in mice designed to identify mutations that perturb DA homeostasis. With a genetic background sensitized by a mutation in the dopamine transporter (DAT), we used random chemical mutagenesis and screened for mutant mice with locomotor abnormalities. Four mutant lines were identified with quantitatively elevated levels of locomotor activity. Mapping of mutations in these lines identified two loci that alter activity only when dopamine levels are elevated by a DAT mutation and thus would only have been uncovered by this type of approach. One of these quantitative trait loci behaves as an enhancer of DA neurotransmission, whereas the other may act as a suppressor. In addition, we also identified three loci which are not dependent on the sensitized background but which also contribute to the overall locomotor phenotype.

Animals↗

Power and sample size for ordered categorical data.

We propose a new method for computing power and sample size for linear rank tests of differences between two ordered multinomial populations. The method is flexible in that it is applicable to any general alternative hypothesis and for any choice of rank scores. We show that the method, though asymptotic, closely approximates existing exact methods. At the same time it overcomes the computational limitations of the exact methods. This advantage makes our asymptotic approach more practical for sample size computations at the planning stages of a large study. We illustrate the method with data arising from both proportional and non-proportional odds models in the two ordered multinomial setting.

Biometry↗