Journal
GENOME BIOLOGY
Volume 21, Issue 1, Pages -Publisher
BMC
DOI: 10.1186/s13059-020-02052-w
Keywords
-
Funding
- National Natural Science Foundation of China [31702087, 31672391, 31701144]
- Key project of the National Natural Science Foundation of China [31790414]
- National Swine Industry Technology System [CARS-35]
Ask authors/readers for more resources
Advances in high-throughput sequencing technologies have reduced the cost of genotyping dramatically and led to genomic prediction being widely used in animal and plant breeding, and increasingly in human genetics. Inspired by the efficient computing of linear mixed model and the accurate prediction of Bayesian methods, we propose a machine learning-based method incorporating cross-validation, multiple regression, grid search, and bisection algorithms named KAML that aims to combine the advantages of prediction accuracy with computing efficiency. KAML exhibits higher prediction accuracy than existing methods, and it is available at https://github.com/YinLiLin/KAML.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available