
Examples
You can use the following sample parameter files as templates for creating
new genetic models. Note that the simulated data output file format is
determined by the driver.
Example 1
In this example we generate a single quantitative trait due to one two-allele
locus tightly linked (recombination fraction 0.05) to a two-allele marker
locus. One sample of 100 nuclear families is generated. Each family has
two parents and three offspring. Seventy percent of the variation in the
trait is due to a single major locus, with 30% of the variation due to
random effects.
Example 1 input parameter file Example 1 data output
Example 2
In this example we generate a single quantitative trait due to one two-allele
locus not linked to a second two-allele locus. This example is nearly identical
to Example 1 except that the recombination fraction between the first and
second loci is 0.50.
Example 2 input parameter file Example 2 data output
Example 3
In this example we generate a single quantitative trait due to one two-allele
locus tightly linked to a six-allele marker locus. One sample of 100 nuclear
families is generated. Each family has two parents and three offspring.
Thirty percent of the variation in the trait is due to a single major locus,
with 70% of the variation due to random effects.
Example 3 input parameter file Example 3 data output
Example 4
In this example we generate a quantitative trait due to a polygenic
component and two two-allele loci. Each trait locus is linked to a different
two-allele marker locus. One sample of 100 nuclear families is generated.
Each family has two parents and three offspring. Four two-allele loci are
generated in two linkage groups. Locus1 and marker1 are in the first linkage
group; locus2 and marker2 are in the second. The distances between loci
are: pterm - locus1 0.5; locus1 - marker1 0.05; marker1 - locus2 0.50;
locus2 - marker2 0.05. Thirty percent of the variation of the trait is
due to locus1, 30% to locus3 and 30% to a trait-specific random effect.
The remaining 10% of the variation of the trait is due to a polygenic component.
Example 4 input parameter file Example 4 data output
Example 5
In this example we generate two quantitative traits, each due to a different
major locus, but with a common polygenic component, and different trait-specific
random effects. Otherwise the model is similar to Example 4.
Example 5 input parameter file Example 5 data output
Example 6
In this example we generate a single quantitative trait due to a random
("covariate") effect. We generate one sample of 20 simple pedigrees,
each having random sibship size but a total of 30 family members.
Example 6 input parameter file Example 6 data output
Example 7
In this example we generate three tightly linked marker loci, one of
which could be used as a qualitative trait. One sample of 20 "CEPH"
type pedigrees with fixed offspring size of 3 is generated.
Example 7 input parameter file Example 7 data output
Example 8
In this example we generate a single quantitative trait due to two unlinked
major loci, a polygenic component, a common sibship environment, and a
trait-specific random effect. One sample of 100 random size sibships
is generated.
Example 8 input parameter file Example 8 data output
Example 9
In this example we generate a derived qualitative trait that has an
underlying genetic liability that is identical to the quantitative trait
generated in Example 1. The derived trait is considered to be "affected"
if the normally distributed genetic liability is greater than 1.64, so
that approximately 5% of the population is affected.
Example 9 input parameter file Example 9 data output
Example 10
In this example we generate a single qualitative trait due to a two-allele
locus which is linked to markers 4, 5, and 6. Markers 1, 2, and 3 are part
of a different linkage group, as are markers 7, 8, 9, and 10. This example
imitates a small "genome screen" situation.
Example 10 input parameter file Example 10 data output
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