The aim of the study is to explore the association of distinctive facial features with candidate genes reported to be associated with facial development.

We intend to replicate the findings reported by Claes et al 2014 where the authors found an association of 20 genes with distinctive facial features. This study uses a novel technique bootstrapped response-based imputation modelling to explore the relationships of sex, genomic ancestry and a set of craniofacial candidate genes. The procedure will be replicated on 4747 3D 15 year old facial shells. In addition an additional 30 genes which did not show any association in Claes' sample of 592 will be explored using the ALSPAC cohort.

Essentially the proposed method uses dense spatially dense quasi-landmarks on 3D images (greater than 7,000), principal component analyses and a new partial least squares regression (bootstrapped response-based imputation modelling (BRIM) to measure and model facial variation.

By simultaneously modeling facial shape variation as a function of sex and genomic ancestry along with genetic markers in craniofacial candidate genes, the effects of sex and ancestry can be removed from the model thereby providing the ability to extract the effects of individual genes.