Tree scanning: A method for using haplotype trees in phenotype/genotype association studies

Alan R. Templeton, Taylor Maxwell, David Posada, Jari H. Stengård, Eric Boerwinkle, Charles F. Sing

Research output: Contribution to journalArticlepeer-review

Abstract

We use evolutionary trees of haplotypes to study phenotypic associations by exhaustively examining all possible biallelic partitions of the tree, a technique we call tree scanning. If the first scan detects significant associations, additional rounds of tree scanning are used to partition the tree into three or more allelic classes. Two worked examples are presented. The first is a reanalysis of associations between haplotypes at the Alcohol Dehydrogenase locus in Drosophila melanogaster that was previously analyzed using a nested clade analysis, a more complicated technique for using haplotype trees to detect phenotypic associations. Tree scanning and the nested clade analysis yield the same inferences when permutation testing is used with both approaches. The second example is an analysis of associations between variation in various lipid traits and genetic variation at the Apolipoprotein E (APOE) gene in three human populations. Tree scanning successfully identified phenotypic associations expected from previous analyses. Tree scanning for the most part detected more associations and provided a better biological interpretative framework than single SNP analyses. We also show how prior information can be incorporated into the tree scan by starting with the traditional three electrophoretic alleles at APOE. Tree scanning detected genetically determined phenotypic heterogeneity within all three electrophoretic allelic classes. Overall, tree scanning is a simple, powerful, and flexible method for using haplotype trees to detect phenotype/genotype associations at candidate loci.

Original languageEnglish
Pages (from-to)441-453
Number of pages13
JournalGenetics
Volume169
Issue number1
DOIs
StatePublished - Jan 2005
Externally publishedYes

ASJC Scopus subject areas

  • General Medicine

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