Quantitative trait nucleotide analysis using bayesian model selection

John Blangero, Harald H H Göring, Jack W. Kent, Jeff T. Williams, Charles P. Peterson, Laura Almasy, Thomas D. Dyer

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Although much attention has been given to statistical genetic methods for the initial localization and fine mapping of quantitative trait loci (QTLs), little methodological work has been done to date on the problem of statistically identifying the most likely functional polymorphisms using sequence data. In this paper we provide a general statistical genetic framework, called Bayesian quantitative trait nucleotide (BQTN) analysis, for assessing the likely functional status of genetic variants. The approach requires the initial enumeration of all genetic variants in a set of resequenced individuals. These polymorphisms are then typed in a large number of individuals (potentially in families), and marker variation is related to quantitative phenotypic variation using Bayesian model selection and averaging. For each sequence variant a posterior probability of effect is obtained and can be used to prioritize additional molecular functional experiments. An example of this quantitative nucleotide analysis is provided using the GAW12 simulated data. The results show that the BQTN method may be useful for choosing the most likely functional variants within a gene (or set of genes). We also include instructions on how to use our computer program, SOLAR, for association analysis and BQTN analysis.

Original languageEnglish (US)
Pages (from-to)829-847
Number of pages19
JournalHuman Biology
Volume81
Issue number5-6
DOIs
StatePublished - Dec 2009
Externally publishedYes

Fingerprint

Bayes Theorem
Bayesian analysis
Bayesian theory
quantitative traits
Nucleotides
nucleotides
polymorphism
genetic polymorphism
functional status
gene
Quantitative Trait Loci
phenotypic variation
quantitative analysis
Genes
quantitative trait loci
Software
genes
software
methodology
analysis

Keywords

  • Bayesian quantitative trait nucleotide (BQTN) analysis
  • Model averaging
  • Sequence data
  • Single nucleotide polymorphisms
  • Statistical genomics

ASJC Scopus subject areas

  • Genetics
  • Genetics(clinical)
  • Ecology, Evolution, Behavior and Systematics

Cite this

Blangero, J., Göring, H. H. H., Kent, J. W., Williams, J. T., Peterson, C. P., Almasy, L., & Dyer, T. D. (2009). Quantitative trait nucleotide analysis using bayesian model selection. Human Biology, 81(5-6), 829-847. https://doi.org/10.3378/027.081.0625

Quantitative trait nucleotide analysis using bayesian model selection. / Blangero, John; Göring, Harald H H; Kent, Jack W.; Williams, Jeff T.; Peterson, Charles P.; Almasy, Laura; Dyer, Thomas D.

In: Human Biology, Vol. 81, No. 5-6, 12.2009, p. 829-847.

Research output: Contribution to journalArticle

Blangero, J, Göring, HHH, Kent, JW, Williams, JT, Peterson, CP, Almasy, L & Dyer, TD 2009, 'Quantitative trait nucleotide analysis using bayesian model selection', Human Biology, vol. 81, no. 5-6, pp. 829-847. https://doi.org/10.3378/027.081.0625
Blangero J, Göring HHH, Kent JW, Williams JT, Peterson CP, Almasy L et al. Quantitative trait nucleotide analysis using bayesian model selection. Human Biology. 2009 Dec;81(5-6):829-847. https://doi.org/10.3378/027.081.0625
Blangero, John ; Göring, Harald H H ; Kent, Jack W. ; Williams, Jeff T. ; Peterson, Charles P. ; Almasy, Laura ; Dyer, Thomas D. / Quantitative trait nucleotide analysis using bayesian model selection. In: Human Biology. 2009 ; Vol. 81, No. 5-6. pp. 829-847.
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