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Statistical Analysis of Data from Gene Frequency Perturbation Experiments
Author(s) -
Wilson S. R.,
Oakeshott J. G.
Publication year - 1985
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/bimj.4710270603
Subject(s) - population , perturbation (astronomy) , gene selection , selection (genetic algorithm) , statistics , population size , statistical analysis , mathematics , computer science , statistical physics , biology , gene , artificial intelligence , genetics , physics , gene expression , demography , quantum mechanics , sociology , microarray analysis techniques
Data from gene frequency perturbation experiments are being used to resolve the selectionistneutralist debate over the evolutionary significance of electrophoretic enzyme variation. Previous statistical analyses of such data have encountered the major difficulty that the effective population size is not known. In this article, we give the statistical theory for fitting various selection models, and we evaluate the known asymptotic results by simulation. We also show that there is further information in data from these experiments besides the estimates of the selection parameters, namely estimates of the bounds for the effective population sizes.