If you chose to do a permutation test [Churchill and DoergeChurchill and Doerge1994] for the purpose of estimating experiment specific threshold values, Zmapqtl will create two auxiliary files to store interim comparisonwise and experimentwise test statistics. If the filename stem is ``qtlcart'' and the model for analysis is ``6'', then these files will be qtlcart.z6c and qtlcart.z6e. The former file should look something like this:
#Row Chrom Mark Position Original P-Val Count -perm 899 -start 1 1 1 0.00010 0.00000 0.982202 883 2 1 1 0.02010 0.00000 0.976641 878 . . .whose columns are
The second file, qtlcart.z6e, will contain two columns of numbers: the permutation and the maximal likelihood ratio over the genome in that permutation. Each permutation will add a line to the output. When enough permutations have been done, Eqtl can be run to summarize the experimentwise levels. A small table will be written to the log file that looks like:
-start Performed 899 permutations of the phenotypes and genotypes Here are the Experimentwise significance levels for different alpha Permutation significance level for alpha = 0.1 : 11.6858 Permutation significance level for alpha = 0.05 : 13.3108 Permutation significance level for alpha = 0.025 : 14.6669 Permutation significance level for alpha = 0.01 : 16.8008 -end of shuffling results
For each shuffle, the largest likelihood ratio test statistic over all test positions is saved in the file. At the end of the shuffling, these maximum values are sorted, and the th largest is the experimentwise significance level for a test of size . The number of permutations can be changed from 899 to any integer from 0 to 10,000. This upper bound could be made higher by changing the appropriate definition in the Main.h source file and recompiling. In general, we find that 1000 permutations is a sufficient number. In a test, values of 1000 and 17,000 were used with little difference in the ultimate comparisonwise and experimentwise values.