Statistical analysis of nuclear genome size of plants with flow cytometer data.
BACKGROUND
There is a mismatch between the sophistication of the cytometer and the resulting data, made possible by the computing power of today, and the traditional statistical methods based on the computing power of the early 1930s. The purpose here is to apply modern statistical techniques that similarly take advantage of this computer power.


METHODS
Likelihood functions and their graphs are introduced as direct measures of plausibility of the parameters of interest. These methods are valid for samples of any size. They are exemplified on an experimental plant flow cytometer data set with n = 2 replications.


RESULTS
The likelihood functions revealed important features of the data that would have been missed by the traditional methods, and in fact would invalidate them.


CONCLUSIONS
The likelihood function produced highly informative graphs that allow quantitative comparisons of different aspects of 2C DNA nuclear contents among different groups or varieties of plants.
Díaz-Francés
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Centro de Investigación en Matemáticas, Department of Probability and Statistics, Guanajuato, Mexico. diazfran@cimat.mx
Sprott
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DA
D000704:Analysis of Variance; D018744:DNA, Plant / Q000032:analysis*; D005434:Flow Cytometry / Q000706:statistics & numerical data*; D018745:Genome, Plant; D016013:Likelihood Functions; D008957:Models, Genetic; D015233:Models, Statistical; D011003:Ploidies
D018744:DNA, Plant