12.2 Sample multivar parameter file

The pedigree file for PolyEM programs is similar to that for other MORGAN programs. The first three entries in each line consist of the individual's name, father's name and mother's name. Integers starting with the fourth column (usually gender) can be fixed effects (gender, age class, etc.) or discrete phenotypes.

For quantitative traits, real numbers follow the names and integers. These real numbers represent trait measurements. Missing values are coded with integer part `999', such as 999.5 in the following example.

Here is part of the pedigree file `polyem.ped'. This file can be found in the `PolyEM' subdirectory of `MORGAN_Examples'.

input pedigree size 90 input pedigree record names 3 integers 3 reals 2 **************************************** 1 0 0 1 1 0 0.0246 -1.0125 2 0 0 2 1 0 -0.5978 1.5963 3 0 0 1 1 0 -0.8124 0.5662 4 0 0 2 1 0 0.4334 1.7721 5 1 2 1 1 0 0.1802 -1.4672 6 1 2 1 1 0 -1.7557 0.8091 7 3 4 2 1 0 999.5 999.5 8 3 4 2 1 0 1.9128 0.9780 9 0 0 2 1 0 0.9530 2.3473 ...

Below is the example multivar parameter file, `polyem.par'. In this example, the starting values are chosen to be close to the final values obtained from an earlier run.

input pedigree file `polyem.ped' select trait 1 start trait 1 mean 0.06515 select trait 2 effects 1 2 start trait 2 mean 1.80671 start trait 2 effect 1 -0.76589 0.58353 start trait 2 effect 2 -0.99161 -0.55306 1.15920 start residual variance 1.10 0.65 start additive variance 0.037 0.0288 start residual covariance -0.09 start additive covariance -0.0017 fit environmental model # for multivar limit EM iterations 200 output spacing 20 EM iterations

The `start trait mean' statements indicate that the first trait is the first real number in the pedigree file, with starting mean value 0.06515 and the second trait is in the second column with starting mean value 1.80671. Note that each trait is identified by a `select trait' statement, which is followed by one or more `start trait mena' statements. @cindex fixed effects The `select trait 2' statement specifies that, for trait 2, two fixed effects (also called covariates) are to be modeled. The `1 2' in this statement gives fixed effect value locations starting with column 4 in the pedigree file. Important: a fixed effect location of `1' indicates that the effect value will be found in column 4. In this example, the fixed effects are to be found in columns 4 and 5. The most commonly modeled fixed effect is gender, which, if present, resides in column 4 of a MORGAN pedigree file.

In this example, the first fixed effect has two levels with starting values -0.76589 and 0.58353. The second effect has three levels with corresponding starting values specified in the `start trait' statement. The starting values represent deviations from the global mean and they are normalized so that the weighted (by the number of individuals in that level) sum is zero to achieve identifiability. The pedigree file column corresponding to a given fixed effect, may take values between zero (to indicate a missing value) and the number of levels assigned to that effect (inclusive) in the `start trait' statement. Any other values in that column will not trigger an error. multivar will simply assume that an additional level exists, but no starting value was assigned to it by the user. Be sure to read the output comments to verify that the number of levels present in the file was as intended.

Initial values for additive and residual variances and covariances are specified in the next four statements. These statements are required. In the variance statements, the number of arguments must be the same as the number of traits selected and they go in order of increasing trait number. In the covariance statements, the number of arguments must be the same as the number of pairs of traits selected. See multivar segregation model parameters, for discussion of the order of arguments.

In the `fit environmental model' statement, we ask multivar to fit a purely environmental model, with no genetic variance. This null hypothesis model is produced in additional to the genetic/environmental model.

The final two statements specify the number of EM iterations and how often the EM estimates are printed out.