Estimation of genomic prediction accuracy from reference populations with varying degrees of relationship.

ABSTRACT: Genomic prediction is emerging in a wide range of fields including animal and plant breeding, risk prediction in human precision medicine and forensic. It is desirable to establish a theoretical framework for genomic prediction accuracy when the reference data consists of information sources with varying degrees of relationship to the target individuals. A reference set can contain both close and distant relatives as well as 'unrelated' individuals from the wider population in the genomic prediction. The various sources of information were modeled as different populations with different effective population sizes (Ne). Both the effective number of chromosome segments (Me) and Ne are considered to be a function of the data used for prediction. We validate our theory with analyses of simulat

SUBMITTER: Lee SH 

PROVIDER: S-EPMC5739427 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature