A twin-pronged attack on complex traits

  title={A twin-pronged attack on complex traits},
  author={Nicholas G. Martin and Dorret I. Boomsma and Geoffrey Machin3},
  journal={Nature Genetics},
Before one starts the hunt for quantitative trait loci (QTLs) for a complex trait it is necessary to show that the trait is genetically influenced. This evidence is most likely to come from the classical twin study—the demonstration that monozygotic twins are more similar for the trait than dizygotic twins. The strengths and weaknesses of twin studies are discussed, and it is suggested that, far from becoming irrelevant with advances in molecular biology, they can improve the efficiency of QTL… 

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    American journal of human genetics
  • 1990
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