Table 1.
Characteristics of preconditioned (deflated) coefficient matrices, and of PCG and DPCG methods for solving ssSNPBLUP applied to the reduced dataset
MS | PCG | 1 | 1 | 1 | 1499 | |||
MS | PCG | 1 | 2 | 0.5 | 1103 | |||
MS | PCG | 1 | 3.3 | 0.3 | 862 | |||
MS | PCG | 1 | 560 | |||||
MS | PCG | 1 | 417 | |||||
MS | PCG | 1 | 608 | |||||
MS | PCG | 1 | 1254 | |||||
MS | PCG | 1 | 2350 | |||||
MS | PCG | 1 | 557 | |||||
MS | PCG | 1 | 416 | |||||
MS | PCG | 1 | 606 | |||||
MS | PCG | 1 | 1254 | |||||
MS | PCG | 1 | 2367 | |||||
MS | DPCG (1) | 1 | 1 | 1 | 6.44 | 294 | ||
MS | DPCG (1) | 1 | 6.44 | 293 | ||||
MS | DPCG (5) | 1 | 1 | 1 | 6.44 | 342 | ||
MS | DPCG (5) | 1 | 6.44 | 331 | ||||
MS | DPCG (5) | 1 | 6.44 | 385 | ||||
MS | DPCG (5) | 1 | 6.44 | 544 | ||||
MS | DPCG (5) | 1 | 6.44 | 961 | ||||
MS | DPCG (5) | 1 | 6.44 | 1456 | ||||
Liu | PCG | 1 | 1 | 1 | 1401 | |||
Liu | PCG | 1 | 561 | |||||
Liu | PCG | 1 | 563 | |||||
Liu | PCG | 1 | 1154 | |||||
Liu | DPCG (5) | 1 | 1 | 1 | 6.44 | 419 | ||
Liu | DPCG (5) | 1 | 6.44 | 399 | ||||
Liu | DPCG (5) | 1 | 6.44 | 520 | ||||
Liu | DPCG (5) | 1 | 6.44 | 1046 |
MS = ssSNPBLUP model proposed by Mantysaari and Stranden [7]; Liu = ssSNPBLUP model proposed by Liu et al. [5]
Number of SNP effects per subdomain is within brackets
Parameters used for the second-level preconditioner
Smallest and largest eigenvalues of the preconditioned (deflated) coefficient matrix
Condition number of the preconditioned (deflated) coefficient matrix
Number of iterations. A number of iterations equal to 10,000 means that the method failed to converge within 10,000 iterations