Biometry and Population Genetics
Recent research results:
Accurate marker effect estimates of genome-wide prediction approaches are important for applications like the detection or functional analysis of genes and the prediction of the performance of crosses. We suggested ridge regression approaches with heteroscedastic marker variances and investigated their properties with respect to prediction accuracy, computational efficiency and accuracy of marker effect estimates (Hofheinz and Frisch 2014).
Introgression libraries are valuable resources for QTL detection and breeding, but their development is costly and time-consuming. We designed selection strategies for the development of maize introgression populations with a limited number of individuals and high-throughput marker assays for DH and S2 crossing schemes (Herzog et al. 2014).