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Minimac was run after phasing both reference and validation populations with Beagle, disregarding pedigree information.
Genotyping a large number of animals at high-density and subsequently imputing the whole-genome sequence information from a small number of carefully selected 'key animals' might lead to even higher accuracy, since imputation quality strongly depends on the marker density in both reference and validation populations [ 34, 37, 38].
By analyzing groups of functionally related genes, we were able to study the same biological processes in both reference and validation datasets, even though not all genes involved in these processes were present, and the number and nature of the represented genes varied in the respective datasets.
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PLAU in particular seems to correlate well with unfavourable outcome, and in this study PLAU correlated well with metastatic HNSCC in both the reference and validation datasets.
For each individual, the most likely genotypes were used and they were assumed to be unphased, for both the reference and validation sets.
Pre-phasing the genotypes of both the reference and validation populations not only provided highly accurate imputed genotypes but was also computationally efficient.
Pre-phasing the genotypes of both the reference and validation populations not only results in highly accurately imputed genotypes but is also computationally efficient.
Phasing both the reference and validation populations with Beagle and subsequent haplotype-based genotype imputation with Minimac outperformed all other approaches, especially when the number of reference animals was small.
It will not matter whether this dataset is a training / reference or both training / reference and validation / candidate set, since the matrix Z can indicate it correctly.
The objective of splitting the reference and validation populations based on sex was to have both breeds represented in each population without any overlapping individuals.
The results are compared to the Correlation Ratio Method (CRM) for reference and validation.
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CEO of Professional Science Editing for Scientists @ prosciediting.com