From: Improving accuracy of genomic prediction by genetic architecture based priors in a Bayesian model
Datasets | Traitsa | N | Min. | Mean | Max. | S.D. | CV% |
---|---|---|---|---|---|---|---|
Dairy cattle | MY | 5024 | −3.383 | 0.000 | 3.319 | 1.000 | – |
MFP | 5024 | −3.569 | 0.000 | 4.281 | 1.000 | – | |
SCS | 5024 | −4.462 | 0.000 | 3.469 | 1.000 | – | |
Loblolly Pine | HT | 927 | −287.700 | 20.300 | 226.10 | 73.315 | 361.158 |
HTLC | 927 | −94.110 | 3.304 | 89.080 | 24.976 | 755.932 | |
BHLC | 927 | −1.578 | 0.092 | 1.573 | 0.507 | 551.087 | |
DBH | 927 | −5.439 | 0.294 | 1.349 | 4.150 | 1411.565 | |
CWAL | 927 | −91.190 | 2.443 | 130.800 | 27.326 | 1118.543 | |
CWAC | 927 | −140.600 | 2.276 | 157.000 | 42.033 | 1846.793 | |
BD | 927 | −0.608 | −0.004 | 1.739 | 0.249 | −6225.000 | |
BA | 927 | −24.560 | −0.261 | 21.140 | 7.315 | −2802.682 | |
Rootnum_bin | 927 | −0.779 | 0.107 | 0.602 | 0.258 | 241.121 | |
Rootnum | 927 | −2.422 | 0.321 | 4.368 | 0.960 | 299.065 | |
Rust_bin | 927 | −0.482 | −0.014 | 0.822 | 0.399 | −2850.000 | |
Rust_gall_vol | 927 | −1.175 | −0.022 | 5.212 | 1.132 | −5145.454 | |
Stiffness | 927 | −3.244 | 0.095 | 6.082 | 1.225 | 1289.474 | |
Lignin | 927 | −3.644 | 0.050 | 4.073 | 1.200 | 2400.000 | |
LateWood | 927 | −4.544 | 0.090 | 4.878 | 1.571 | 1745.556 | |
Density | 927 | −10.290 | −0.053 | 17.610 | 2.498 | −4713.208 | |
C5C6 | 927 | −8.102 | −0.049 | 9.057 | 2.649 | −5406.122 |