Table 3 Estimates of bias when using the ESM and GWAM chip obtained from regressing phenotypes for the TST population on BV predicted using LDA and LDLA composite relationship matrices using different \(\uplambda\) values
From: Use and optimization of different sources of information for genomic prediction
ESM | GWAM | |||
|---|---|---|---|---|
LDA | LDLA | LDA | LDLA | |
\(\uplambda = 0\) | 0.71 (0.08) | 0.73 (0.08) | 0.71 (0.08) | 0.77 (0.08) |
\(\uplambda = 0.1\) | 0.71 (0.08) | 0.72 (0.08) | 0.62 (0.07) | 0.67 (0.07) |
\(\uplambda = 0.2\) | 0.71 (0.08) | 0.71 (0.08) | 0.58 (0.07) | 0.63 (0.07) |
\(\uplambda = 0.3\) | 0.70 (0.07) | 0.71 (0.08) | 0.56 (0.07) | 0.60 (0.07) |
\(\uplambda = 0.4\) | 0.70 (0.07) | 0.70 (0.07) | 0.54 (0.07) | 0.58 (0.07) |
\(\uplambda = 0.5\) | 0.69 (0.07) | 0.69 (0.07) | 0.52 (0.07) | 0.56 (0.07) |
\(\uplambda = 0.6\) | 0.68 (0.07) | 0.69 (0.07) | 0.51 (0.07) | 0.53 (0.07) |
\(\uplambda = 0.7\) | 0.68 (0.07) | 0.68 (0.07) | 0.49 (0.07) | 0.51 (0.07) |
\(\uplambda = 0.8\) | 0.68 (0.07) | 0.68 (0.07) | 0.47 (0.07) | 0.49 (0.07) |
\(\uplambda = 0.9\) | 0.68 (0.07) | 0.68 (0.07) | 0.46 (0.07) | 0.46 (0.07) |
\(\uplambda = 1\) | 0.68 (0.08) | 0.68 (0.07) | 0.44 (0.07) | 0.44 (0.07) |