DOI: 10.5061/dryad.8df69
title: Data from: Incorporating single-step strategy into random regression model to enhance genomic prediction of longitudinal trait

description: In prediction of genomic values, single-step method has been demonstrated
 to outperform multi-step methods. In statistical analyses of longitudinal
 traits, random regression test-day model (RR-TDM) has clear advantages
 over other models. Our goal in this study was to evaluate the performance
 of the model integrating both single-step and RR-TDM prediction methods,
 called single-step random regression test-day model (SS RR-TDM), in
 comparison with the pedigree-based RR-TDM and genomic best linear unbiased
 prediction (GBLUP) model. We performed extensive simulations to exploit
 potential advantages of SS RR-TDM over the other two models under various
 scenarios with different level of heritability, the number of QTL as well
 as the selection scheme. SS RR-TDM was found to achieve the highest
 accuracy and unbiasedness under all scenarios, exhibiting robust
 prediction ability in longitudinal trait analyses. Moreover, SS RR-TDM
 showed better persistency of accuracy over generations than GBLUP model.
 In addition, we also found that the SS RR-TDM had advantages over RR-TDM
 and GBLUP in terms of a real dataset of human contributed by the GAW18
 workshop. The findings in our study firstly proved the feasibility and
 advantages of the SS RR-TDM, and further enhanced strategies for the
 genomic prediction of longitudinal traits in the future.
description: simulated data under the
 scenario where heritability is 0.5This package includes
 longitudinal data simulated under the scenario where heritability is 0.5.
 Files include pedigree file (ped), genotypic file (geno), phenotypic file
 (phe) and files containing true genetic value (tbv).h2-0.5.zipsimulated data under the scenario where the number of QTL is 10This package includes longitudinal data simulated under the scenario where the number of QTL is 10. Files include pedigree file (ped), genotypic file (geno), phenotypic file (phe) and files containing true genetic value (tbv).QTL10.zipsimulated data under the scenario where heritability is 0.1This package includes longitudinal data simulated under the scenario where heritability is 0.1. Files include pedigree file (ped), genotypic file (geno), phenotypic file (phe) and files containing true genetic value (tbv).h2-0.1.zipsimulated data under the scenario where the number of QTL is 500This package includes longitudinal data simulated under the scenario where the number of QTL is 500. Files include pedigree file (ped), genotypic file (geno), phenotypic file (phe) and files containing true genetic value (tbv).QTL500.zipsimulated genotypic data of replicates 1-7 under the scenario where males were selected based on predicted genetic valueThis package includes simulated genotypic data under the scenario where males were selected based on predicted genetic value. The genotypic data were those from replicates 1-7.non-random-sel-ped-phe-tbv.zipnon-random-sel-geno-1-7.zipsimulated genotypic data of replicates 15-20 under the scenario where males were selected based on predicted genetic valueThis package includes simulated genotypic data under the scenario where males were selected based on predicted genetic value. The genotypic data were those from replicates 15-20.non-random-sel-geno-15-20.zipsimulated data under the scenario where males were selected based on predicted genetic valueThis package includes longitudinal data simulated under the scenario where males were selected based on predicted genetic value. Files include pedigree file (ped), phenotypic file (phe) and files containing true genetic value (tbv).non-random-sel-ped-phe-tbv.zipsimulated data under the default scenarioThis package includes longitudinal data simulated under the default scenario. Files include pedigree file (ped), phenotypic file (phe) and files containing true genetic value (tbv).default-ped-phe-tbv.zipsimulated genotypic data of replicates 8-14 under the scenario where males were selected based on predicted genetic valueThis package includes simulated genotypic data under the scenario where males were selected based on predicted genetic value. The genotypic data were those from replicates 8-14.large-refpop-geno-1-10.zipnon-random-sel-geno-8-14.zipsimulated genotypic data of 5 000 individuals from replicates 11-20 under the default scenarioThis package includes genotypic data simulated under the default scenario. The genotypic data were from replicates 11-20. For each replicate, genotypic data were from training individuals and a larger training set compared to the default one.large-refpop-geno-11-20.zipsimulated genotypic data of 5 000 individuals from replicates 1-10 under the default scenarioThis package includes genotypic data simulated under the default scenario. The genotypic data were from replicates 1-10. For each replicate, genotypic data were from training individuals and a larger training set compared to the default one.large-refpop-geno-1-10.zipsimulated genotypic data under the default scenarioThis package includes genotypic data simulated under the default scenario. The genotypic data were from replicates 1-7.default-geno-1-7.zipsimulated genotypic data under the default scenarioThis package includes genotypic data simulated under the default scenario. The genotypic data were from replicates 8-14.default-geno-8-14.zipsimulated genotypic data under the default scenarioThis package includes genotypic data simulated under the default scenario. The genotypic data were from replicates 15-20.default-geno-15-20.zipgeneration files for simulated data under six scenariosGeneration files for simulated data under the six scenariosgeneration.zip