... genetics.¹

Although it gets a lot more complicated when you're dealing with tens or hundreds of markers, and you don't even know which ones belong on which chromosomes!

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... analysis.²

We're going to run an association analysis instead.

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... markers.³

Remember that $AA$ is 2, $Aa$ is 1, and $aa$ is 0, so a positive relationship means that $A$ is associated with increased values of the trait.

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... trait.⁴

I'm getting this from the columns for H3:a, H3:d, and R2(0:3), respectively, for reasons I'll explain in class.

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... mapping]⁵

I'll bet you knew there was a Bayesian version coming, didn't you?

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... variance,⁶

Remember that for composite interval mapping, we fit a regression of phenotype on backgrnound genotype before running the analysis. The residual variance is the variance not explained by this regression.

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... variance.⁷

The total variance is just what it says, the total observed phenotypic variance. $1-r^2$ is the proportion of phenotypic variance accounted for by the QTL at this position.

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... variance.⁸

$1-r^2_t$ is the proportion of phenotypic variance accounted for by the QTL at this position and the background genotype.

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....⁹

$S$ is distributed as a $\chi^2$ with two degrees of freedom.

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