Detection and localization of a single binary trait locus in experimental populations.

Published

Journal Article

The advancements made in molecular technology coupled with statistical methodology have led to the successful detection and location of genomic regions (quantitative trait loci; QTL) associated with quantitative traits. Binary traits (e.g. susceptibility/resistance), while not quantitative in nature, are equally important for the purpose of detecting and locating significant associations with genomic regions. Existing interval regression methods used in binary trait analysis are adapted from quantitative trait analysis and the tests for regression coefficients are tests of effect, not detection. Additionally, estimates of recombination that fail to take into account varying penetrance perform poorly when penetrance is incomplete. In this work a complete probability model for binary trait data is developed allowing for unbiased estimation of both penetrance and recombination between a genetic marker locus and a binary trait locus for backcross and F2 experimental designs. The regression model is reparameterized allowing for tests of detection. Extensive simulations were conducted to assess the performance of estimation and testing in the proposed parameterization. The proposed parameterization was compared with interval regression via simulation. The results indicate that our parameterization shows equivalent estimation capabilities, requires less computational effort and works well with only a single marker.

Full Text

Duke Authors

Cited Authors

  • McIntyre, LM; Coffman, CJ; Doerge, RW

Published Date

  • August 2001

Published In

  • Genet Res

Volume / Issue

  • 78 / 1

Start / End Page

  • 79 - 92

PubMed ID

  • 11556139

Pubmed Central ID

  • 11556139

Digital Object Identifier (DOI)

  • 10.1017/s0016672301005092

Language

  • eng

Conference Location

  • England