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. 2019 Jun 25;51:30. doi: 10.1186/s12711-019-0472-8

Table 1.

Characteristics of preconditioned (deflated) coefficient matrices, and of PCG and DPCG methods for solving ssSNPBLUP applied to the reduced dataset

Modela Methodb kOc kSc kO/kS λmind λmaxd κe Nf
MS PCG 1 1 1 1.07×10-04 1.81×102 1.70×106 1499
MS PCG 1 2 0.5 1.07×10-04 9.11×101 8.55×105 1103
MS PCG 1 3.3 0.3 1.07×10-04 5.51×101 5.17×105 862
MS PCG 1 101 10-1 1.07×10-04 1.91×101 1.79×105 560
MS PCG 1 102 10-2 1.07×10-04 1.19×101 1.12×105 417
MS PCG 1 103 10-3 1.06×10-04 1.19×101 1.12×105 608
MS PCG 1 104 10-4 4.86×10-05 1.19×101 2.45×105 1254
MS PCG 1 105 10-5 4.87×10-06 1.19×101 2.45×106 2350
MS PCG 10-1 1 10-1 1.07×10-03 1.91×102 1.79×105 557
MS PCG 10-2 1 10-2 1.07×10-02 1.19×103 1.12×105 416
MS PCG 10-3 1 10-3 1.06×10-01 1.19×104 1.12×105 606
MS PCG 10-4 1 10-4 4.86×10-01 1.19×105 2.45×105 1254
MS PCG 10-5 1 10-5 4.86×10-01 1.19×106 2.45×106 2367
MS DPCG (1) 1 1 1 1.09×10-04 6.44 5.93×104 294
MS DPCG (1) 1 105 10-5 1.09×10-04 6.44 5.92×104 293
MS DPCG (5) 1 1 1 1.07×10-04 6.44 6.03×104 342
MS DPCG (5) 1 101 10-1 1.07×10-04 6.44 6.03×104 331
MS DPCG (5) 1 102 10-2 1.07×10-04 6.44 6.04×104 385
MS DPCG (5) 1 103 10-3 1.06×10-04 6.44 6.05×104 544
MS DPCG (5) 1 104 10-4 4.96×10-05 6.44 1.30×105 961
MS DPCG (5) 1 105 10-5 4.95×10-06 6.44 1.30×106 1456
Liu PCG 1 1 1 1.06×10-04 6.98×101 6.56×105 1401
Liu PCG 1 101 10-1 1.06×10-04 1.19×101 1.12×105 561
Liu PCG 1 102 10-2 1.06×10-04 1.19×101 1.12×105 563
Liu PCG 1 103 10-3 5.91×10-05 1.19×101 2.02×105 1154
Liu DPCG (5) 1 1 1 1.07×10-04 6.44 6.05×104 419
Liu DPCG (5) 1 101 10-1 1.07×10-04 6.44 6.05×104 399
Liu DPCG (5) 1 102 10-2 1.06×10-04 6.44 6.05×104 520
Liu DPCG (5) 1 103 10-3 6.02×10-05 6.44 1.07×105 1046

aMS = ssSNPBLUP model proposed by Mantysaari and Stranden [7]; Liu = ssSNPBLUP model proposed by Liu et al. [5]

bNumber of SNP effects per subdomain is within brackets

cParameters used for the second-level preconditioner D

dSmallest and largest eigenvalues of the preconditioned (deflated) coefficient matrix

eCondition number of the preconditioned (deflated) coefficient matrix

fNumber of iterations. A number of iterations equal to 10,000 means that the method failed to converge within 10,000 iterations