5) Next, answer the question "Do you want to retain all populations for further analysis"?
If your answer is No, then Delete Populations dialog box pops up for your selection ofpopulations to be deleted.
6) If you selected Groups at step (3), enter the number of groups in enter the number ofgroups dialog box;
Click OK to open Group Populations dialog box for grouping of populations and selectappropriate populations for each group.
(7) If Two-locus LD was checked at step (3), then you need to select a significance level(P) to test for linkage disequilibria between pairs of loci. Important: A high P valuecan result in an extremely large output when you have a large number ofalleles/locus, loci and populations!!! In most cases, P ≤ 0.05 should be used.
(8) If Neutrality Test was checked at step (3), then you need to select the number ofsimulations for computing 95% lower and upper confidence limits used to test forneutrality.We recommend 500 - 1000 simulations for a reliable estimation of theseconfidence limits.
(9) If you have correctly completed steps (1) to (8), then you are prompted withresult.dat output Window, displaying the results from the analysis you just chose.Activate the menu File | Save as... to save the output into an ASCII file for further use orcut-and-paste selected text directly into a Window-based word processing package, suchas Microsoft Word or WordPerfect.
This is a Diploid Data Analysis dialog box for dominant markers. You are prompted tochoose between HW equilibrium (i.e., FIS = 0) or HW disequilibrium (i.e., FIS ≠ 0).Notice that in your data, you can specify FISvalue for each population. If you do not havean input for FIS, the program will assume that the population is in HW equilibrium. When you select HW disequilibrium at the prompt, the program will read your FISvalue and useit when estimating allele frequency. If you have FISvalue for each population but select HW equilibrium, the program will ignore your FISvalue and assume HW equilibrium.
All other aspects of data analysis for dominant markers are similar to that described forco-dominant markers.
