You can also use Prune to simulate missing data. You set the amount of missing marker data you would like to simulate with the -M option. This will be a percent, and should be specified before you invoke the bootstrap option, which actually does the simulation. Use a value of 3 to tell Prune to randomly set some of the markers to missing. Over the entire data set, approximately the percentage of markers that had been set with the -M option will be set to -10. The results will be in a file with the filename extension ``.crb''. Similar to simulating missing data, some of the markers can be made dominant by using a value of 4 with the bootstrap option. The percentage of markers transformed is set with the -M. The direction of dominance is random: Half of those changed will convert the allele to dominant, while the other half will convert the allele.
If you use a value of 5 with -b and specify a percentage for -M, then you can investigate how selective genotyping compares to having typed all the individuals. As an example, suppose you have a data set typed for 500 individuals and use -M 20 and -b 5. The individuals are ordered with respect to the trait of interest and those whose trait values are in the lowest 10% are retained along with those in the highest 10%. Those in the 10 to 90 percent range are deleted. A new data set with the ``.crb'' filename extension will contain the results.