Robust heritability estimation in plant studies

V. M. Lourenço, Paulo C. Rodrigues, Miguel dos Santos Fonseca, Ana M. Pires

Research output: Contribution to conferencePaper


Heritability is of major importance in plant studies to help achieve better yield and other agronomic traits of
interest. In candidate gene studies regression models are used to test for associations between phenotype and
candidate single nucleotide polymorphisms (SNPs). SNP imputation guarantees that marker information
is complete and so both the coefficient of determination, R 2 , and broad-sense heritability are equivalent.
However, when the normality assumption is violated, the classical R 2 may be seriously affected. Recently
two R 2 alternatives with good properties were proposed for the linear mixed model: a marginal R 2 m for the
variance explained by the fixed factors and a conditional R 2 c for the variance explained by both the fixed and
random factors. In this work we step forward a robust version of R 2 c and assess the adequacy of both classical
and robust counterparts in the estimation of true broad-sense heritability via simulation, where a particular
contamination scenario is considered. An example of application with a real maize data set is also presented.
Original languageEnglish
Number of pages6
Publication statusPublished - Jul 2015
Event60th ISI World Statistics Congress - Riocentro, Rio de Janeiro, Brazil
Duration: 26 Jul 201531 Jul 2015


Conference60th ISI World Statistics Congress
CityRio de Janeiro
Internet address


  • Robust linear mixed model
  • Coefficient of determination
  • Single nucleotide polymorphism
  • Heritability estumation


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