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fptest: a sas routine for testing differences in allelic count.

¹Plant Gene Resources of Canada, Saskatoon Research Centre, Agriculture and Agri-Food Canada, 107 Science Place, Saskatoon, SK, Canada S7N 0X2.

Molecular Ecology Resources

|May 14, 2011

Summary

Assessing genetic diversity requires accounting for sample size. A new random permutation method in SAS helps evaluate allelic count differences across variable sample sizes, crucial for genetic diversity studies.

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Area of Science:

Genetics
Bioinformatics
Statistical analysis

Background:

Allelic count is a key metric for genetic diversity.
Allelic count is influenced by sample size, potentially causing estimation bias and complicating significance testing.
Comparing genetic diversity across groups with varying sample sizes presents statistical challenges.

Purpose of the Study:

To introduce a SAS routine utilizing random permutation for assessing allelic count differences.
To address the challenges posed by variable sample sizes in genetic diversity comparisons.
To provide a method for robustly testing the significance of allelic count variations between groups.

Main Methods:

Development of a SAS routine based on random permutation.
Application of the routine to assess allelic count differences among groups of unequal size.
Statistical significance testing of allelic count variations.

Main Results:

The SAS routine effectively assists in the assessment of allelic count differences.
The method allows for reliable comparison of genetic diversity across samples of varying sizes.
Demonstrated application in examining allelic count differences in Canadian oat cultivars across eight breeding periods.

Conclusions:

Random permutation offers a viable solution for comparing allelic counts in samples of different sizes.
The developed SAS routine provides a valuable tool for genetic diversity analysis in plant breeding and population genetics.
Accurate assessment of genetic diversity is enhanced by methods that account for sample size variations.