Ina Hoeschele

Learn More
MOTIVATION A major challenge of systems biology is to infer biochemical interactions from large-scale observations, such as transcriptomics, proteomics and metabolomics. We propose to use a partial correlation analysis to construct approximate Undirected Dependency Graphs from such large-scale biochemical data. This approach enables a distinction between(More)
Quantitative trait loci (QTL) affecting milk production and health of dairy cattle were mapped in a very large Holstein granddaughter design. The analysis included 1794 sons of 14 sires and 206 genetic markers distributed across all 29 autosomes and flanking an estimated 2497 autosomal cM using Kosambi's mapping function. All families were analyzed jointly(More)
Additive and nonadditive genetic variances were estimated for cow fertility of Holsteins. Measures of fertility were first lactation days open and service period as recorded and with upper bounds of 150 and 91 d, respectively. Six million inseminations from the Raleigh, North Carolina Processing Center were used to form fertility records of 379,009 cows.(More)
Genetic analysis of gene expression in a segregating population, which is expression profiled and genotyped at DNA markers throughout the genome, can reveal regulatory networks of polymorphic genes. We propose an analysis strategy with several steps: (1) genome-wide QTL analysis of all expression profiles to identify eQTL confidence regions, followed by(More)
Our goal is gene network inference in genetical genomics or systems genetics experiments. For species where sequence information is available, we first perform expression quantitative trait locus (eQTL) mapping by jointly utilizing cis-, cis-trans-, and trans-regulation. After using local structural models to identify regulator-target pairs for each eQTL,(More)
The effect of inbreeding on mean and genetic covariance matrix for a quantitative trait in a population with additive and dominance effects is shown. This genetic covariance matrix is a function of five relationship matrices and five genetic parameters describing the population. Elements of the relationship matrices are functions of Gillois (1964) identity(More)
Information on multiple linked genetic markers was used in a Bayesian method for the statistical mapping of quantitative trait loci (QTL). Bayesian parameter estimation and hypothesis testing were implemented via Markov chain Monte Carlo algorithms. Variables sampled were the augmented data (marker-QTL genotypes, polygenic effects), an indicator variable(More)
A residual maximum likelihood method, implemented with a derivative-free algorithm, was derived for estimating position and variance contribution of a single QTL together with additive polygenic and residual variance components. The method is based on a mixed linear model including random polygenic effects and random QTL effects, assumed to be normally(More)
seasons (HYS), sires and progeny per sire were simulated. HYS were generated as fixed, normally distributed or drawn from a proper uniform distribution. The downward bias of the AMML estimator for small family sizes (50 sires, average of 40 progeny) was eliminated with the MCMML estimator. For designs with many HYS, 0.9 incidence, 50 sires and 40 progeny on(More)
For estimation of dominance effects and dominance variance, the inverse of a dominance relationship matrix is required. Dominance effects can be partitioned into sire x dam or sire x maternal grandsire subclass effects that are inherited and residuals within subclass that are not inherited. The subclass effects have immediate use in predicting performance(More)