Unconditional twolocus nonparametric linkage analysis
Lars Ängquist, Dragi Anevski and Holger Luthman
Centre for Mathematical Sciences
Mathematical Statistics
Lund Institute of Technology,
Lund University,
2005
ISSN 14039338

Abstract:

We discuss different aspects of unconditional twolocus nonparametric linkage
(NPL) analysis with special emphasis on genegene interaction. We interpret
this as identicalbydescent (IBD) sharing correlation between two disease
loci both having marginal effect. We relate this to the concept of twolocus
NPL score functions, the possible importance of using a composite rather
than a simple null hypothesis and the corresponding calculation of statistical
power. Moreover, we define several classes of score functions and give multiple
suggestions on how to incorporate a composite null hypothesis into the analysis.
The least favourable twolocus IBDdistribution is discussed, resulting in
an upper bound of the twolocus pvalue.




Key words:

NPL analysis, unconditional twolocus linkage analysis, genetic disease models,
IBDsharing, genegene interaction, score functions, composite null hypothesis,
least favourable distribution, Monte Carlo simulation, estimation of genetic
parameters, power calculations
