Prediction of complex traits: Conciliating genetics and statistics.

TitlePrediction of complex traits: Conciliating genetics and statistics.
Publication TypeJournal Article
Year of Publication2017
AuthorsManfredi, E, Tusell, L, Vitezica, ZG
JournalJ Anim Breed Genet
Date Published2017 Jun

This review focuses on methods used to predict complex traits. Main characteristics of prediction approaches are given: the deterministic or stochastic nature of prediction, the objects of prediction, the sources of information and the main statistical methods. Sources of information discussed are the traditional genealogies and phenotypes, nucleotide sequences, expression data and epigenetics marks. Statistical methods are presented as successive degrees of generalization from the definition of the conditional expectation as the prediction rule, to best linear unbiased prediction, then Bayesian and, recently, machine learning methods, including meta-methods. We highlight the contributions of Daniel Gianola to this methodological evolution.

Alternate JournalJ. Anim. Breed. Genet.
PubMed ID28508479