TY  - JOUR
A1  - Pool, John E.
A1  - Hellmann, Ines
A1  - Jensen, Jeffrey D.
A1  - Nielsen, Rasmus
T1  - Population genetic inference from genomic sequence variation
Y1  - 2010/03/01 
JF  - Genome Research 
JO  - Genome Research 
SP  - 291 
EP  - 300 
DO  - 10.1101/gr.079509.108 
VL  - 20 
IS  - 3 
UR  - http://genome.cshlp.org/content/20/3/291.abstract 
N2  - Population genetics has evolved from a theory-driven field with little empirical data into a data-driven discipline in which genome-scale data sets test the limits of available models and computational analysis methods. In humans and a few model organisms, analyses of whole-genome sequence polymorphism data are currently under way. And in light of the falling costs of next-generation sequencing technologies, such studies will soon become common in many other organisms as well. Here, we assess the challenges to analyzing whole-genome sequence polymorphism data, and we discuss the potential of these data to yield new insights concerning population history and the genomic prevalence of natural selection. 
ER  -