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## Output

Here is a truncated example of the output of Zmapqtl for a backcross.

#      890840384   -filetype Zmapqtl.out
#
#       QTL Cartographer V. 1.13b, March 1998
#       This output file (qtlcart.z) was created by Zmapqtl...
#
#       It is 10:39:44 on Wednesday, 25 March 1998
#
#
#The position is from the left telomere on the chromosome
-window      10.00      Window size for models 5 and 6
-background      5      Background parameters in model 6
-Model           6      Model number
-trait           1      Analyzed trait [Trait_1]
-cross          B2      Cross
#  Test Site   * Like. Ratio Test Statistics   *     Additive
c  m position     H0:H1      R2(0:1)    TR2(0:1)    H1:a        S1
-s
1  1  0.0001      0.411      0.002      0.473      0.027      1.531
1  2  0.0133      0.016      0.000      0.472      0.005      1.542
1  2  0.0333      0.023      0.000      0.472      0.006      1.547
1  2  0.0533      0.031      0.000      0.472      0.008      1.554
1  2  0.0733      0.041      0.000      0.472      0.009      1.563
1  2  0.0933      0.052      0.000      0.472      0.010      1.572
1  2  0.1133      0.063      0.000      0.472      0.011      1.582
1  2  0.1333      0.073      0.000      0.472      0.012      1.593
.
.
.
-e


For a backcross, let be the additive effect. We have two hypotheses:

• : no QTL effect at the test position, i.e.
• : There is a QTL effect at the test position, i.e.
The first eight columns correspond to
1. Chromosome of test position
2. Left flanking marker of test position
3. Absolute position from left telomere, in Morgans.
4. Likelihood ratio test statistic for It is a random variable with one degree of freedom for any position, meaning that a value of 3.84 or higher is evidence for a QTL. The significance level over more positions will be higher due to multiple testing.
5. Estimate of (the additive effect) under
6. Test statistic for the normality of the residuals under
The last 13 columns are not shown because they are only valid for design experiments. They would all be zeros if shown.

The output for an design (or any design in which dominance effects can be estimated) is similar, but has more information. For an , you can estimate additive () and dominance () parameters at each position. Thus, there are four hypotheses.

• : ,
• : ,
• : ,
• : ,
and twelve full columns of output, corresponding to all possible hypothesis tests and parameter estimates. The 21 columns correspond to
1. Chromosome of test position.
2. Left flanking marker of test position.
3. Absolute position from left telomere, in Morgans.
4. Likelihood ratio test statistic for
5. Likelihood ratio test statistic for
6. Likelihood ratio test statistic for
7. Estimate of (the additive effect) under
8. Estimate of (the additive effect) under
9. Estimate of (the dominance effect) under
10. Estimate of (the dominance effect) under
11. Likelihood ratio test statistic for
12. Likelihood ratio test statistic for
13. for
14. for
15. for
16. for
17. for
18. for
19. for
20. for
21. for

Subsections

Next: Permutation Test output Up: Zmapqtl Previous: Permutations, Bootstraps and Jackknives   Contents   Index
Christopher Basten 2002-03-27