title: Location-dependent empirical thresholds for quantitative trait mapping.
abstract: The Churchill-Doerge approach toward constructing empirical thresholds has received widespread use in the genetic mapping literature through the past 16 years. The method is valued for both its simplicity and its ability to preserve the genome-wide error rate at a prespecified level. However, the Churchill-Doerge method is not designed to maintain the local (comparison-wise) error rate at a constant level except in situations that are unlikely to occur in practice. In this article, we introduce the objective of preserving the local error rate at a constant level in the context of mapping quantitative trait loci in linkage populations. We derive a method that preserves the local error rate at a constant level, provide an application via simulation on a Hordeum vulgare population, and demonstrate evidence of the relationship between recombination and location bias. Furthermore, we indicate that this method is equivalent to the Churchill-Doerge method when several assumptions are satisfied.
authors.affiliation: Nature Source Genetics, Ithaca, New York 14850, USA. jlacombe@naturesourcegenetics.com
authors.forename: Jason
authors.initials: J
authors.lastname: LaCombe
authors.forename: Benjamin
authors.initials: B
authors.lastname: McClosky
authors.forename: Steven
authors.initials: S
authors.lastname: Tanksley
mesh_terms: D002874:Chromosome Mapping; D003198:Computer Simulation; D008040:Genetic Linkage; D023281:Genomics / Q000379:methods; D008126:Lod Score; D008957:Models, Genetic; D040641:Quantitative Trait Loci