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Location-dependent empirical thresholds for quantitative trait mapping.

Jason LaCombe1, Benjamin McClosky, Steven Tanksley

  • 1Nature Source Genetics, Ithaca, New York 14850, USA. jlacombe@naturesourcegenetics.com

G3 (Bethesda, Md.)
|September 14, 2012
PubMed
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A new method for quantitative trait loci mapping preserves local error rates, improving upon the Churchill-Doerge approach. This genetic mapping technique offers more accurate results in linkage populations.

Area of Science:

  • Genetics and Genomics
  • Statistical Genetics
  • Bioinformatics

Background:

  • The Churchill-Doerge method is widely used for empirical threshold construction in genetic mapping due to its simplicity and genome-wide error rate control.
  • However, this method does not consistently maintain the local (comparison-wise) error rate, except under rare conditions.
  • This limitation is particularly relevant in quantitative trait loci (QTL) mapping within linkage populations.

Purpose of the Study:

  • To introduce and derive a novel method for QTL mapping that preserves the local error rate at a constant level.
  • To address the shortcomings of the Churchill-Doerge method concerning local error rate control in genetic mapping.
  • To investigate the relationship between recombination and location bias in QTL analysis.

Main Methods:

Keywords:
QTLadjusted P-valueempirical thresholdlocal error ratemultiple hypothesis testing

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  • Development of a new statistical method to ensure a constant local error rate during QTL mapping.
  • Application of the derived method through simulation studies using a Hordeum vulgare (barley) population.
  • Analysis of the relationship between recombination frequency and location bias in the simulated data.

Main Results:

  • The newly derived method successfully preserves the local error rate at a constant level in QTL mapping.
  • Simulations on a Hordeum vulgare population demonstrated the practical application and efficacy of the method.
  • Evidence was found supporting a relationship between recombination rates and location bias in genetic mapping.

Conclusions:

  • The proposed method offers an improvement over the Churchill-Doerge approach by maintaining a constant local error rate.
  • This new method is particularly valuable for QTL mapping in linkage populations where local error control is critical.
  • The method is shown to be equivalent to the Churchill-Doerge method under specific, commonly met assumptions.