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Exact(5)

The importance of relatedness between validation and reference animals was also evaluated for the different chips and methods.

The impact of relatedness between validation and reference animals on imputation accuracy is illustrated in Figure  2.

Other factors, such as genotyping errors [ 36], or degree of relationship between validation and reference groups [ 9, 10, 32], are also important.

In this study, the two pure breeds had similar family structures, which resulted in the distribution of genomic relationships between validation and reference populations being similar for the two breeds.

The impact of genetic relatedness between validation and reference animals on imputation accuracy was assessed by regressing CORR on the average of the top 10 genomic relationships between each animal in the validation set with all the animals in the reference set [ 15].

Similar(55)

Thus, average genomic relationships between the validation and reference populations were similar for Landrace and Yorkshire pigs, as shown in the first two rows of Table  3.

Among the factors that can affect imputation accuracies and were put forward by Iwata and Jannink [ 14], (genomic) relationships between the validation and reference populations constitute a major factor.

However, based on Table  3, it was not obvious that higher genomic relationships between the validation and reference populations would lead to higher imputation accuracies, as was proposed in many other studies, such as [ 3, 25].

Table 1 gives details on the constitution of the different validation and reference populations.

We used the same window for consistency between comparisons to validation results and reference results from Stewart et al. 2011.

Figures  5B and 6B further illustrate the correlations between predicted and reference values for release and yield of the validation set, respectively.

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