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Article

Prediction performance of linear models and gradient boosting machine on complex phenotypes in outbred mice.

G3 (Bethesda, Md.) - 4 Apr 2022

Perez Bruno C, Bink Marco C A M, Svenson Karen L, Churchill Gary A, Calus Mario P L

Abstract excerpt

We compared the performance of linear (GBLUP, BayesB, and elastic net) methods to a nonparametric tree-based ensemble (gradient boosting machine) method for genomic prediction of complex traits in mice. The dataset used contained genotypes for 50,112 SNP markers and phenotypes for 835 animals from 6 generations. Traits analyzed were bone mineral density, body weight at 10, 15, and 20 weeks, fat percentage,...

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PMID: 35166767
DOI: 10.1093/g3journal/jkac039
PMCID: PMC8982369

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