Premium
Strategies for detecting susceptibility genes in a complex disease
Author(s) -
Babron MarieClaude,
Barillot Emmanuel,
MargaritteJeannin Patricia,
ClergetDarpoux Françoise
Publication year - 1999
Publication title -
genetic epidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.301
H-Index - 98
eISSN - 1098-2272
pISSN - 0741-0395
DOI - 10.1002/gepi.1370170777
Subject(s) - linkage disequilibrium , linkage (software) , replicate , biology , genetic association , genetics , haplotype , computational biology , genome scan , genome wide association study , haplotype estimation , nonparametric statistics , genome , statistics , gene , single nucleotide polymorphism , allele , mathematics , genotype , microsatellite
One of the current issues in genetic epidemiology is detecting susceptibility genes on the genome. It is common now to undertake systematic screening of the genome using approaches based on a measure of the haplotype sharing in sib pairs. Here, we compare the efficiency of two statistics, the maximum likelihood score (MLS) and the nonparametric linkage score (NPLa) on the simulated data provided for GAW11. A question often raised is whether it is better to perform a single‐step or a two‐step strategy. For the simulated model, and whatever the strategy used, we show here that the answer is not unequivocal. In both cases, the power to detect susceptibility genes in a single replicate with MLS or NPL is extremely low. With two replicates, only one of the four simulated loci could be detected with reasonable power. When gametic disequilibrium is suspected, methods testing for both linkage and association might be more powerful.