Optimisation of the core subset for the APY approximation of genomic relationships.

ABSTRACT:

Background

By entering the era of mega-scale genomics, we are facing many computational issues with standard genomic evaluation models due to their dense data structure and cubic computational complexity. Several scalable approaches have been proposed to address this challenge, such as the Algorithm for Proven and Young (APY). In APY, genotyped animals are partitioned into core and non-core subsets, which induces a sparser inverse of the genomic relationship matrix. This partitioning is often done at random. While APY is a good approximation of the full model, random partitioning can make results unstable, possibly affecting accuracy or even reranking animals. Here we present a stable optimisation of the core subset by choosing animals with the most informative genotype data.

Me

SUBMITTER: Pocrnic I 

PROVIDER: S-EPMC9682752 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature