We use the basic discussion of Kempthorne (1957 [1969]). Considering only the most basic of genetic models, we can look at the quantitative contribution of a single locus with [genotype]Create? Gi as
where
is the effect of [genotype]Create? Gi
and is the environmental effect.
Consider an experiment with a group of sires and their progeny from random dams. Since the progeny get half of their genes from the father and half from their (random) mother, the progeny equation is
Intraclass correlations
Consider the experiment above. We have two groups of progeny we can compare. The first is comparing the various progeny for an individual sire (called within sire group). The [variance]Create? will include terms for genetic [variance]Create? (since they did not all get the same genotype) and environmental [variance]Create?. This is thought of as an error term.
The second group of progeny are comparisons of means of half sibs with each other (called among sire group). In addition to the error term as in the within sire groups, we have an addition term due to the differences among different means of half sibs. The intraclass correlation is
: ,
since environmental effects are independent of each other.
The ANOVA
In an experiment with sires and progeny per sire, we can calculate the following ANOVA, using as the genetic [variance]Create? and as the environmental variance:
{| class="wikitable"
| + Table 1: ANOVA for Sire experiment |
! Source
! d.f.
! Mean Square
! Expected Mean Square
| - |
| Among sire groups |
|
|
|
| - |
| Within sire groups |
|
|
|
| } |
The term is the intraclass correlation among half sibs. We can easily calculate . The Expected Mean Square is calculated from the relationship of the individuals (progeny within a sire are all half-sibs, for example), and an understanding of intraclass correlations.
See also:
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