Ghost QTL and hotspots in experimental crosses - novel solution by mixed model with nonzero mean

\"Ghost-QTL\" are the false discoveries in QTL mapping, that arise due to the \"accumulation\" of the polygenic effects, uniformly distributed over the genome. The locations on the chromosome which are strongly correlated with the summary polygenic effect depend on a specific sample correlation structure determined by the genotype at all loci. During the analysis of e-QTL data or recombinant inbred lines this correlation structure is preserved for all traits under consideration, and may lead to the so called \"hot-spots\" via the detection of the summary polygenic effect at exactly the same positions for most of the considered traits. We illustrate that the problem can be solved by the application of the extended mixed effect model, where the random effects are allowed to have a nonzero mean. We provide formulas for estimating the thresholds for the corresponding t-test statistics and use them in the stepwise selection strategy, which allows for a simultaneous detection of several QTL. Extensive simulation studies illustrate that our approach allows to eliminate ghost-QTL/false hot spot effects, while preserving a high power of detection of true QTL effects.