What is it about?
Since only estimated effects that pass a "significance" threshold are reported, the magnitude of the effects are biased upwards. We developed a Bayesian method to correct for this bias
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Why is it important?
The literature is full of estimated QTL effects, and as explained the magnitude of the effects reported will generally be biased upwards.
Perspectives
Recently the problem is less important as rather than estimated individual QTL whole genome evaluations is now generally employed in commercial breeding
Dr Joel Ira Weller
ARO, The Volcani Center
Read the Original
This page is a summary of: Correcting for bias in estimation of quantitative trait loci effects, Genetics Selection Evolution, September 2005, Springer Science + Business Media,
DOI: 10.1051/gse:2005013.
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