Introduction to the Special Issue: Genome-Wide Association Studies

far from having run its course. Attention is now turn ing from simple case-control designs to using family data or prospective cohort data that convey a wealth of phenotypic information, including life-course varying phenotypes, as well as environmental exposures. Sta tistical analyses of GWAS data have to date focused mainly on the simplest tests of one SNP at a time, leaving open the possibility that more sophisticated analyses may reveal further important results. These could involve results about metabolic pathways, gene by-gene and gene-by-environment interactions, impu tations and copy number variants. Funds from the US government (National Institutes of Health), the Well come Trust and other research organizations for ge nomic studies have increased substantially. Advances in statistical methodology will be central in these developments, and we proposed this special is sue to help foster them, by authoritative reviews of the current state of the art, and pointers to novel develop ments. Statistical issues and challenges arise from all aspects of design and analysis of GWAS. This special issue consists of 12 papers focusing on the following topics: statistical designs using case-control or family