Skip to main content

Balancing Population Size and Genetic Information in Parentage Analysis Studies

Buy Article:

$43.00 plus tax (Refund Policy)


In parentage analysis studies, the parameters of interest typically are not the parent assignments themselves, but population parameters such as variance in fertility, self-pollination rate, or average dispersal distances. The precision of parameter estimates is affected by two factors: the number of offspring under consideration, and the precision with which the offspring can be assigned to parents. When assignment of parents is based on genetic information, the confidence in assignments is affected by the number and polymorphism of the loci considered, and by the number of potential parents in the population. Studying larger populations may yield higher numbers of offspring, but since larger populations contain more potential parents, more (or more highly polymorphic) loci are necessary to attain a given level of confidence in the parent assignments. This article addresses how to relate the size of the population and the number of loci when designing a study. It is shown that the number of loci needed to assign all offspring unambiguously is proportional to the logarithm of the population size. In some cases, the constant of proportionality can be determined, eliminating the need for simulation-based projections. Population-wide measures of uncertainty in parent assignments are also introduced, and it is shown that holding uncertainty “steady” as the population size increases also requires increasing the number of loci proportional to the logarithm of the population size. Data from a study of self-pollination are used to illustrate the techniques suggested.
No References
No Citations
No Supplementary Data
No Article Media
No Metrics

Keywords: Dispersal; Fertility; Mating; Study design

Document Type: Research Article

Publication date: 01 September 2003

  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more