With hundreds of ancient genomes becoming available this year, ancient DNA research has now entered the genomics era. Utilizing the temporal aspect of these new data, we can now address fundamental evolutionary questions such as the characterization of selection processes shaping the genomes. The temporal dimension in the data has spurred the development in the last 10 years of new methods allowing the detection of loci evolving non-neutrally but also the inference of selection coefficients across genomes capitalizing on these time serial data. To guide empirically oriented researchers towards the statistical approach most appropriate for their data, this article reviews several of those methods, discussing their underlying assumptions and the parameter ranges for which they have been developed. While I discuss some methods developed for experimental evolution, the main focus is ancient DNA.