Maximising knowledge from dense SNP data using multi-locus analysis (2007–2009)
This study aims to derive and apply a new measure of how multiple genes are correlated on a chromosome. Such a measure is important because the correlation structure among genes can be used to infer population dynamics, to estimate genetic relationships between individuals and to map genes affecting specific characters. Previous methods have only considered two genes at a time, which is inefficient. We will apply our new measure to data consisting of many markers and multiple quantitative phenotypes in humans, mice and cattle. Our proposed new method will have applications in population, quantitative and conservation genetics, and in gene mapping studies across species.