BMC Genomics

Table 3 Spearman rank correlations between predicted body weight from the different genome-enabled prediction approaches and for the various sub-sampling of the entire training dataset

From: Would large dataset sample size unveil the potential of deep neural networks for improved genome-enabled prediction of complex traits? The case for body weight in broilers

Predictive approach	Training dataset size (%)
Predictive approach	1	3	5	7	10	15	20	30	40	50	60	70	80	90	100
BRR x Bayes Cπ	0.99	0.99	0.99	0.99	0.99	0.99	0.99	0.99	0.98	0.98	0.98	0.98	0.98	0.98	0.98
BRR x DNN	0.79	0.89	0.86	0.95	0.95	0.96	0.78	0.97	0.94	0.91	0.94	0.95	0.95	0.95	0.94
BRR x BRR-WT	0.33	0.52	0.64	0.69	0.78	0.83	0.87	0.91	0.94	0.95	0.96	0.96	0.96	0.97	0.97
BRR x Bayes Cπ-WT	0.33	0.52	0.63	0.69	0.79	0.83	0.85	0.90	0.93	0.93	0.95	0.95	0.95	0.96	0.96
Bayes Cπ x DNN	0.79	0.89	0.86	0.96	0.95	0.95	0.78	0.95	0.93	0.88	0.93	0.94	0.94	0.93	0.94
Bayes Cπ x BRR-WT	0.32	0.52	0.64	0.69	0.78	0.82	0.86	0.90	0.93	0.93	0.94	0.95	0.95	0.95	0.96
Bayes Cπ x Bayes Cπ-WT	0.32	0.52	0.63	0.69	0.80	0.82	0.85	0.90	0.93	0.94	0.95	0.95	0.96	0.97	0.97
DNN x BRR-WT	0.33	0.52	0.58	0.66	0.76	0.79	0.71	0.88	0.89	0.87	0.92	0.92	0.93	0.92	0.92
DNN x Bayes Cπ-WT	0.33	0.52	0.57	0.66	0.76	0.79	0.69	0.87	0.87	0.86	0.90	0.91	0.92	0.91	0.91
BRR-WT x Bayes Cπ-WT	0.99	0.99	0.99	0.99	0.99	0.99	0.98	0.98	0.98	0.97	0.99	0.98	0.98	0.98	0.98

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ISSN: 1471-2164

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