Population genetic inference from genomic sequence variation

John E. Pool, Ines Hellmann, Jeffrey Jensen, Rasmus Nielsen

Research output: Contribution to journalReview article

145 Citations (Scopus)

Abstract

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.

Original languageEnglish (US)
Pages (from-to)291-300
Number of pages10
JournalGenome Research
Volume20
Issue number3
DOIs
StatePublished - Mar 2010
Externally publishedYes

Fingerprint

Population Genetics
Genome
Accidental Falls
Metagenomics
Genetic Selection
History
Technology
Costs and Cost Analysis

ASJC Scopus subject areas

  • Genetics
  • Genetics(clinical)

Cite this

Population genetic inference from genomic sequence variation. / Pool, John E.; Hellmann, Ines; Jensen, Jeffrey; Nielsen, Rasmus.

In: Genome Research, Vol. 20, No. 3, 03.2010, p. 291-300.

Research output: Contribution to journalReview article

Pool, John E. ; Hellmann, Ines ; Jensen, Jeffrey ; Nielsen, Rasmus. / Population genetic inference from genomic sequence variation. In: Genome Research. 2010 ; Vol. 20, No. 3. pp. 291-300.
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