4.7 Article

Two simple methods to improve the accuracy of the genomic selection methodology

Related references

Note: Only part of the references are listed.
Article Genetics & Heredity

Partial Least Squares Enhances Genomic Prediction of New Environments

Osval A. Montesinos-Lopez et al.

Summary: Improved prediction of future seasons or new environments is crucial for plant breeding. This study demonstrates that the partial least squares regression method outperforms the Bayesian genomic best linear unbiased predictor method in predicting future seasons or new environments.

FRONTIERS IN GENETICS (2022)

Article Genetics & Heredity

A Comparison of Three Machine Learning Methods for Multivariate Genomic Prediction Using the Sparse Kernels Method (SKM) Library

Osval A. Montesinos-Lopez et al.

Summary: Genomic selection has revolutionized the way plant breeders select genotypes, using statistical machine learning models to predict phenotypic values of new lines. Multi-trait genomic prediction models leverage correlated traits to improve accuracy. This paper compares the performance of three multi-trait methods and finds that their performance varies under different predictors.

GENES (2022)

Article Genetics & Heredity

Multi-trait genome prediction of new environments with partial least squares

Osval A. Montesinos-Lopez et al.

Summary: The genomic selection methodology has revolutionized plant breeding by using statistical machine learning algorithms to predict candidate individuals. However, it faces challenges when predicting future seasons or new environments. This study compared the performance of the multi-trait partial least square (MT-PLS) regression method with the Bayesian Multi-trait Genomic Best Linear Unbiased Predictor (MT-GBLUP) method and found that MT-PLS outperforms MT-GBLUP in predicting future seasons or new environments.

FRONTIERS IN GENETICS (2022)

Article Biochemical Research Methods

Gene selection using hybrid dragonfly black hole algorithm: A case study on RNA-seq COVID-19 data

Elnaz Pashaei et al.

Summary: The paper introduces a new hybrid approach for solving gene selection problem by combining the strengths of two existing metaheuristics. The proposed approach reduces dimensionality of feature space using MRMR filter method and utilizes a hybrid DBH algorithm to determine a smaller set of significant genes, showing significant improvement in classification accuracy compared to existing methods. The method was also tested on real RNASeq coronavirus-related gene expression data and demonstrated promise in selecting most discriminative genes with high accuracy.

ANALYTICAL BIOCHEMISTRY (2021)

Article Plant Sciences

Genome-based prediction of multiple wheat quality traits in multiple years

Maria Itria Ibba et al.

PLANT GENOME (2020)

Review Biochemistry & Molecular Biology

Enhancing Genetic Gain through Genomic Selection: From Livestock to Plants

Yunbi Xu et al.

PLANT COMMUNICATIONS (2020)

Review Agronomy

Genomic Selection in Cereal Breeding

Charlotte D. Robertsen et al.

AGRONOMY-BASEL (2019)

Review Plant Sciences

Genomic Selection in Plant Breeding: Methods, Models, and Perspectives

Jose Crossa et al.

TRENDS IN PLANT SCIENCE (2017)

Article Plant Sciences

Prospects for Genomic Selection in Cassava Breeding

Marnin D. Wolfe et al.

PLANT GENOME (2017)

Article Plant Sciences

Genome-Enabled Prediction Models for Yield Related Traits in Chickpea

Manish Roorkiwal et al.

FRONTIERS IN PLANT SCIENCE (2016)

Article Genetics & Heredity

LinkImpute: Fast and Accurate Genotype Imputation for Nonmodel Organisms

Daniel Money et al.

G3-GENES GENOMES GENETICS (2015)

Article Genetics & Heredity

Genome-Wide Regression and Prediction with the BGLR Statistical Package

Paulino Perez et al.

GENETICS (2014)

Article Multidisciplinary Sciences

TASSEL-GBS: A High Capacity Genotyping by Sequencing Analysis Pipeline

Jeffrey C. Glaubitz et al.

PLOS ONE (2014)

Review Plant Sciences

Genomic selection: genome-wide prediction in plant improvement

Zeratsion Abera Desta et al.

TRENDS IN PLANT SCIENCE (2014)

Article Multidisciplinary Sciences

A Robust, Simple Genotyping-by-Sequencing (GBS) Approach for High Diversity Species

Robert J. Elshire et al.

PLOS ONE (2011)

Article Agriculture, Dairy & Animal Science

Efficient Methods to Compute Genomic Predictions

P. M. VanRaden

JOURNAL OF DAIRY SCIENCE (2008)

Article Biochemical Research Methods

TASSEL: software for association mapping of complex traits in diverse samples

Peter J. Bradbury et al.

BIOINFORMATICS (2007)