International Biometric Society Statistical Methods for the Detection of Positive Selection using Genome Maps

The genetic makeup of a population reflects its demographic history and the effects of selection. An expanding population will show less genetic variation than a population of the same, but constant, size. This effect is visible across the genome as a whole. A selective sweep occurs when a positive mutation spreads through a population. Neutral alleles which are strongly linked to this mutation also spread through the population. This process is known as hitchhiking and leads to low genetic variation around the site of the mutation. Classical tests, such as Tajima’s [4], are based on genetic information from a small section of the genome and thus cannot differentiate between the effects of demography and positive selection. Advances in the mapping of single nucleotide polymorphisms (SNPs) enable us to differenti-ate between the local action of positive selection and the genome wide effect of demographic changes. Nielsen et al. [2] propose a test for detecting selective sweeps by looking for appropri-ate changes in genetic variation from the background level. Such a test has been shown to be powerful. However, the level of mutation varies across the genome and without comparing with related populations or subpopulations it may be unclear whether a very low level of variation in a section of the genome indicates the positive selection has occurred or that there is a lo