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AUTOMATIC ACTIONS

There are a number of automatic actions that can be performed using the -b option. You will use one of the numbers below with the option to tell Prune to do that action. A new dataset is then printed to a file stem.crb, where stem is the filename stem. Note that if you give a nonzero value to this option, the interactive flag is turned off.

  1. Perform a bootstrap resampling of the data. Sampling of individuals is done with replacement to create a sample of the same size as the original.

  2. Permute the the traits against genotype arrays. If there are multiple traits in the data set, then each trait will be shuffled against the genotype arrays.

  3. Simulate missing markers. The percent of missing marker data should be specified with the -M option, and it should be an number in the range of 0 to 100 percent.

  4. Simulate dominant markers. The percent of dominant marker data should be specified with the -M option, and it should be an number in the range of 0 to 100 percent. The direction of dominance is random.

  5. Simulate selective genotyping. The percent of typed individuals should be specified with the -M option, and it should be an number in the range of 0 to 100 percent. This will print out individuals with trait values in the tails of the overall distribution. The value specified will be the sum of these tails: Each tail will have half of the total. This will apply to whichever trait was last analyzed, or trait 1 if all the traits had been analyzed. It is probably best to do this with single trait data sets.

  6. Permute the the traits against genotype arrays. A value of 12 does this as well. If there are multiple traits in the data set, then entire trait arrays will be shuffled against the genotype arrays. This contrasts with option 2 above which permutes the traits independently. If you think the traits are correlated and you want to maintain that correlation, use this option. Otherwise, use option 2.

  7. Prune the data back to one trait. Use the -t option with a trait number to select the trait. The output will have one trait: All individuals with missing values for this trait will also be deleted.

  8. Prune the data to specified traits. Use the -t option with a trait number to select the trait. If the original data has t traits, then an integer in the range [1,t] will eliminate all but the specified trait, that is it will do exactly the same thing as option 7 above. If an integer less than one is used, then only traits whose names begin with a plus sign will remain in the output. If greater than the number of traits, then any trait whose name begins with a minus sign will be eliminated. Once the traits are eliminated, all individuals with missing data for any of the surviving traits will also be deleted.


next up previous contents index
Next: EXAMPLES Up: PRUNE Previous: INPUT FORMAT   Contents   Index
Christopher Basten 2002-03-27