Novel Mathematical and Statistical methods for extracting information from genetic data

Project description

Secondary Supervisors: Sian Bray (Biosciences), Cyril Rauch (Vet School)

With modern genetic sequencing, there is a mass of genetic data available. In determining the effects of genetic variations on physical characteristics (phenotypes), it is appealing to think there is a gene for 'X'. However, in reality, many phenotypic traits depend rather weakly on many genes a.k.a. small gene effects linked to complex phenotypic traits. The aim of this project is to develop mathematical and statistical tools to extract, from real data, these weak associations between phenotype and genotype. A range of statistical and mathematical modelling tools will be used to analyse the shape of distributions, correlations, using ideas from Shannon information theory. Initial data comes from the Bray-lab who are working on the ion uptake and equilibration in Arabidopsis -a model plant whose genome is well-sequenced. (This project is available as part of the BBSRC DTP).