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Background  Large-scale genome-wide association studies are promising for unraveling the genetic basis of complex diseases. Population structure is a potential problem, the effects of which on genetic association studies are controversial. The first step to systematically quantify the effects of population structure is to choose an appropriate measure of population structure for human data. The commonly used measure is  Wright's  F ST . For a set of subpopulations it is generally assumed to be one value of F ST . However, the estimates could be different for distinct loci. Since population structure is a concept at the population level, a measure of population structure that utilized the information across loci would be desirable.    Findings  In this study we propose an  adjusted C parameter  according to the sample size from each sub-population. The new measure C is based on the  c parameter  proposed for SNP data, which was assumed to be subpopulation-specific and common for all loci. In this study, we performed extensive simulations of samples with varying levels of population structure to investigate the properties and relationships of both measures. It is found that the two measures generally agree well.    Conclusion  The new measure simultaneously uses the marker information across the genome. It has the advantage of easy interpretation as one measure of population structure and yet can also assess population differentiation.

A new measure of population structure using multiple single nucleotide polymorphisms and its relationship with FST