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A simple regression-based method to map quantitative trait loci underlying function-valued phenotypes.

Kwak IY, Moore CR, Spalding EP, Broman KW - Genetics (2014)

Bottom Line: However, multiple phenotypes are commonly measured, and recent technological advances have greatly simplified the automated acquisition of numerous phenotypes, including function-valued phenotypes, such as growth measured over time.While methods exist for QTL mapping with function-valued phenotypes, they are generally computationally intensive and focus on single-QTL models.After identifying multiple QTL by these approaches, we can view the function-valued QTL effects to provide a deeper understanding of the underlying processes.

View Article: PubMed Central - PubMed

Affiliation: Department of Statistics, University of Wisconsin, Madison, Wisconsin 53706.

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Signed LOD scores from single-QTL genome scans, with each time point considered individually.
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Related In: Results  -  Collection


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fig1: Signed LOD scores from single-QTL genome scans, with each time point considered individually.

Mentions: We first applied interval mapping by Haley–Knott regression (Haley and Knott 1992), considering each time point individually. The results are displayed in Figure 1, with the x-axis representing genomic position and the y-axis representing time, and so each horizontal slice is a genome scan for one time point. We plot a signed LOD score, with the sign representing the estimated direction of the QTL effect: Red indicates that lines with the Cvi allele had a higher phenotype average than the lines with the Ler allele; blue indicates that lines with the Ler allele had a higher phenotype average than the lines with the Cvi allele.


A simple regression-based method to map quantitative trait loci underlying function-valued phenotypes.

Kwak IY, Moore CR, Spalding EP, Broman KW - Genetics (2014)

Signed LOD scores from single-QTL genome scans, with each time point considered individually.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4125409&req=5

fig1: Signed LOD scores from single-QTL genome scans, with each time point considered individually.
Mentions: We first applied interval mapping by Haley–Knott regression (Haley and Knott 1992), considering each time point individually. The results are displayed in Figure 1, with the x-axis representing genomic position and the y-axis representing time, and so each horizontal slice is a genome scan for one time point. We plot a signed LOD score, with the sign representing the estimated direction of the QTL effect: Red indicates that lines with the Cvi allele had a higher phenotype average than the lines with the Ler allele; blue indicates that lines with the Ler allele had a higher phenotype average than the lines with the Cvi allele.

Bottom Line: However, multiple phenotypes are commonly measured, and recent technological advances have greatly simplified the automated acquisition of numerous phenotypes, including function-valued phenotypes, such as growth measured over time.While methods exist for QTL mapping with function-valued phenotypes, they are generally computationally intensive and focus on single-QTL models.After identifying multiple QTL by these approaches, we can view the function-valued QTL effects to provide a deeper understanding of the underlying processes.

View Article: PubMed Central - PubMed

Affiliation: Department of Statistics, University of Wisconsin, Madison, Wisconsin 53706.

Show MeSH