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Efficient genomic prediction based on whole-genome sequence data using split-and-merge Bayesian variable selection.

Mario P L CalusAniek C BouwmanChris SchrootenRoel F Veerkamp
Published in: Genetics, selection, evolution : GSE (2016)
The split-and-merge approach splits one large computational task into many much smaller ones, which allows the use of parallel processing and thus efficient genomic prediction based on whole-genome sequence data. The split-and-merge approach did not improve prediction accuracy, probably because we used data on a single breed for which relationships between individuals were high. Nevertheless, the split-and-merge approach may have potential for applications on data from multiple breeds.
Keyphrases
  • electronic health record
  • big data
  • copy number
  • gene expression
  • machine learning
  • dna methylation
  • risk assessment
  • data analysis
  • amino acid
  • deep learning