Computing power of quantitative trait locus association mapping for haploid loci

Derek Gordon; Andrew R. Zinn

doi:10.1186/1471-2105-10-261

Computing power of quantitative trait locus association mapping for haploid loci

Research output: Contribution to journal › Article › peer-review

Abstract

Background: Statistical power calculations are a critical part of any study design for gene mapping. Most calculations assume that the locus of interest is biallelic. However, there are common situations in human genetics such as X-linked loci in males where the locus is haploid. The purpose of this work is to mathematically derive the biometric model for haploid loci, and to compute power for QTL mapping when the loci are haploid. Results: We have derived the biometric model for power calculations for haploid loci and have developed software to perform these calculations. We have verified our calculations with independent mathematical methods. Conclusion: Our results fill a need in power calculations for QTL mapping studies. Furthermore, failure to appropriately model haploid loci may cause underestimation of power.

Original language	English (US)
Article number	261
Journal	BMC Bioinformatics
Volume	10
DOIs	https://doi.org/10.1186/1471-2105-10-261
State	Published - Aug 23 2009

ASJC Scopus subject areas

Structural Biology
Biochemistry
Molecular Biology
Computer Science Applications
Applied Mathematics

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10.1186/1471-2105-10-261

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title = "Computing power of quantitative trait locus association mapping for haploid loci",

abstract = "Background: Statistical power calculations are a critical part of any study design for gene mapping. Most calculations assume that the locus of interest is biallelic. However, there are common situations in human genetics such as X-linked loci in males where the locus is haploid. The purpose of this work is to mathematically derive the biometric model for haploid loci, and to compute power for QTL mapping when the loci are haploid. Results: We have derived the biometric model for power calculations for haploid loci and have developed software to perform these calculations. We have verified our calculations with independent mathematical methods. Conclusion: Our results fill a need in power calculations for QTL mapping studies. Furthermore, failure to appropriately model haploid loci may cause underestimation of power.",

author = "Derek Gordon and Zinn, {Andrew R.}",

note = "Funding Information: The authors gratefully acknowledge grant NIH NS35554 to ARZ. Also, the authors gratefully acknowledge the help of Dr. Tara Matise, who created the home page for their software.",

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AU - Zinn, Andrew R.

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N2 - Background: Statistical power calculations are a critical part of any study design for gene mapping. Most calculations assume that the locus of interest is biallelic. However, there are common situations in human genetics such as X-linked loci in males where the locus is haploid. The purpose of this work is to mathematically derive the biometric model for haploid loci, and to compute power for QTL mapping when the loci are haploid. Results: We have derived the biometric model for power calculations for haploid loci and have developed software to perform these calculations. We have verified our calculations with independent mathematical methods. Conclusion: Our results fill a need in power calculations for QTL mapping studies. Furthermore, failure to appropriately model haploid loci may cause underestimation of power.

AB - Background: Statistical power calculations are a critical part of any study design for gene mapping. Most calculations assume that the locus of interest is biallelic. However, there are common situations in human genetics such as X-linked loci in males where the locus is haploid. The purpose of this work is to mathematically derive the biometric model for haploid loci, and to compute power for QTL mapping when the loci are haploid. Results: We have derived the biometric model for power calculations for haploid loci and have developed software to perform these calculations. We have verified our calculations with independent mathematical methods. Conclusion: Our results fill a need in power calculations for QTL mapping studies. Furthermore, failure to appropriately model haploid loci may cause underestimation of power.

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Computing power of quantitative trait locus association mapping for haploid loci

Abstract

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