Use of regularized quantile regression to predict the genetic merit of pigs for asymmetric carcass traits

Patricia Mendes Dos Santos,Paulo Sávio Lopes,Fabyano Fonseca E Silva,Rodrigo Reis Mota,Ana Carolina Campana Nascimento,Camila Ferreira Azevedo,Moysés Nascimento,Simone Eliza Facioni Guimarães

doi:10.1590/s0100-204x2018000900004

Patricia Mendes Dos Santos, Paulo Sávio Lopes + Show 6 more

Open Access

https://doi.org/10.1590/s0100-204x2018000900004

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Abstract

Abstract: The objective of this work was to evaluate the use of regularized quantile regression (RQR) to predict the genetic merit of pigs for asymmetric carcass traits, compared with the Bayesian lasso (Blasso) method. The genetic data of the traits carcass yield, bacon thickness, and backfat thickness from a F2 population composed of 345 individuals, generated by crossing animals from the Piau breed with those of a commercial breed, were used. RQR was evaluated considering different quantiles (τ = 0.05 to 0.95). The RQR model used to estimate the genetic merit showed accuracies higher than or equal to those obtained by Blasso, for all studies traits. There was an increase of 6.7 and 20.0% in accuracy when the quantiles 0.15 and 0.45 were considered in the evaluation of carcass yield and bacon thickness, respectively. The obtained results are indicative that the regularized quantile regression presents higher accuracy than the Bayesian lasso method for the prediction of the genetic merit of pigs for asymmetric carcass variables.

Highlights

In Brazil, the pork market stands out, with a production of approximately 3.6 million tons of meat in 2015 (ABPA, 2015)
The objective of this work was to evaluate the use of regularized quantile regression (RQR) to predict the genetic merit of pigs for asymmetric carcass traits, compared with the Bayesian lasso (Blasso) method
The obtained results are indicative that the regularized quantile regression presents higher accuracy than the Bayesian lasso method for the prediction of the genetic merit of pigs for asymmetric carcass variables

Summary

Introduction

In Brazil, the pork market stands out, with a production of approximately 3.6 million tons of meat in 2015 (ABPA, 2015). The distribution of many of these traits presents asymmetric behavior; in this case, the usual methods of genomic selection, based on conditional expectations, E(Y|X), besides making it. Impossible to predict all distributions of phenotypic values, may under- or overestimate the marker effects This occurs because, in these situations, the mean may not be the best measure to represent data distribution and, the generated estimates may lead to mistakes in the selection of animals

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