Additive and multiplicative genome-wide association models identify genes associated with growth

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Standard genome-wide association studies evaluate the association between single nucleotide polymorphisms (SNPs or Genotype G) and phenotype (e.g. growth) conditional on non-SNP covariates including environmental factors (E, e.g. diet) or population stratification, on an additive fashion. For traits known to be the result of genotype-by-environment interactions (GxE), like growth, a multiplicative model could potentially uncover additional SNPs that influence growth on a context-dependent (e.g. diet or breed) fashion. The objective of this study was to assess and compare the performance of context-independent (additive, G+E) and context-dependent (multiplicative, G+E+GxE) models to identify polymorphisms and corresponding genes associated with growth that are context-independent and context-dependent. In addition to single-SNP analysis, a multi-SNP haplotype-based analysis that can increase the precision of the estimates was evaluated for the additive model.

Original languageEnglish (US)
Title of host publication2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2011
Pages975-977
Number of pages3
DOIs
StatePublished - Dec 1 2011
Event2011 IEEE International Conference onBioinformatics and Biomedicine Workshops, BIBMW 2011 - Atlanta, GA, United States
Duration: Nov 12 2011Nov 15 2011

Publication series

Name2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2011

Other

Other2011 IEEE International Conference onBioinformatics and Biomedicine Workshops, BIBMW 2011
CountryUnited States
CityAtlanta, GA
Period11/12/1111/15/11

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management

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