Work Code

The Work Code must be specified with an eight (8) letter string. Each letter in the string is a flag to tell the program whether to do a certain step. Some of the flags have options to modify the behavior of that step. The eight letter string starts from position 0 and continues on to position 7. In general, a lower case letter indicates that the function should be skipped, while an upper case letter tells MImapqtl to do the step. The labels on the items below indicate the positions.

0.

Scan flag

This can take on values S or s. If S, then MImapqtl will go into scan mode, that is it will scan the genome for a new QTL beginning with any model. At the end of this scan, it will print out a likelihood profile for the existence of a new QTL. The user can then plot the values and decide where to place a new QTL.

1.

Model flag

This flag tells MImapqtl whether to use the initial model specified with the -E option. If M, then MImapqtl will begin its analysis with the initial model. If m, then it will start the analysis from a state with no QTL. If you use m, then you should also specify prt in positions 2, 3 and 4. For example, smprtSEC would make sense: It would search for QTL de novo.

2.

Parameter flag

Use a P here if you want MImapqtl to re-estimate the paramters in the initial model. Use a p if you want to skip this step. The case of this position should almost always match that of position 1: It makes little sense to estimate parameters in a model without any parameters.

3.

Refine postion flag

Use an R here if you want MImapqtl to refine the position estimates in the initial model. Use an r if you want to skip this step. If you don't have an initial model, then this should be r. This is most useful if your initial model was generated from a run of Zmapqtlor JZmapqtl. The R value causes the position to be optimized within the current interval. If you want to extend the refinement to adjacent intervals, use A.

4.

Test flag

For initial models, you may want to test the significance of all parameters before searching for new QTL. Use a T here if you want MImapqtl to test the significance of the parameters in the initial model. Use a t if you want to skip this step. If you don't have an initial model, then this should be t. This position also allows you to test the dominance effects alone: You can use D in place of T. Finally, you can test the current set of epistatic interactions by using a E in this position.

5.

Search flag

Use an S here if you want MImapqtl to search for more QTL. Use an s if you want to skip this step. You can also specify an A if you only want to search for the additive effects of putative QTL (that is, don't search for dominance effects in crosses with three marker genotypes). Finally, if you use a D here, MImapqtl will only search for dominance effects at putative QTL locations that don't already have them.

6.

Epistasis flag

Use an E here if you want MImapqtl to search for epistatic effects. Use an e if you want to skip this step. If you want to use a backward elimination approach, then use a B in this position. The backward elimination approach will only be used if the number of possible interactions plus the number of main effects is less than $2\sqrt{n}$. If you want to relax this restriction, then use a U in place of the B.

7.

Covariance flag

Use a C here if you want MImapqtl to calculate the variance-covariance matrix, $r^2$ values and breeding values for the final model. Use a c if you want to skip this step. You may also use an R in this position. In that case, MImapqtl will calculate the residuals for the final model, replace the trait values with the residuals and print out a new data set with the same markers to a file (stem.res by default, where stem is the filename stem). If the phase variable is set to a number $N$ greater than zero, then the residual data set will be written to stemPhaseN.res. The C and R options are mutally exclusive.

The default work code is smprtSeC, which searches for QTL starting with an initial model containing no QTL. If you want to do an analysis withan initial model, then sMPRTSeC would be appropriate. For a scan to find a new QTL, you might use SMPrtSec recursively, adding a QTL in each step.

If you have a model and simply want to create a new data set with the residuals replacing the traits, then use sMPrtseR as the work code.