CBLUP90IOD2 is a threshold-linear program for obtaining solutions to very large models. Solutions are obtained by iteration on data using the preconditioned conjugate iteration.

• Original linear model program BLUPF90 (I. Misztal)
• Rewrite to threshold-linear model program CBLUP90 (I. Misztal)
• Rewrite to multiple linear traits with computed thresholds and multiple linear traits(B. Auvray)
• Rewrite of BLUPF90 to iteration on data: BLUP90IOD (S. Tsuruta)

CBLUP90IOD2 supports models with one categorical trait and multiple linear traits. Thresholds are computed but none of the variances is. Memory requirements are about 56 bytes per equation.

The first trait must be categorical and not be missing.

OPTION category 3

Number of categories (default 2)

OPTION conv_crit 1d-12

Convergence criterion (default 1d-12).

OPTION maxrounds 500

Maximum rounds (default 5000).

OPTION pcg_maxrounds 40

Set the maximum number of PCG rounds (default 40).

OPTION cont

Keep the last solutions and residuals for restart. When the program does not converge, you will have “solutions_rsd”. This option requires this file for restart.

OPTION cont 1

Restart the program from the last run using the previous solutions.

OPTION thresholds t1 t2 ... 0

Give thresholds for categorical traits (the last threshold = 0).

OPTION avgeps

Use the average eps / PCG rounds for convergence. With this option, solutions will be more stable.

OPTION SNP_file snp

Specify the SNP file name to use genotype data.

parameter file: ex1.par

DATAFILE
ex1.dat
NUMBER_OF_TRAITS
 3
NUMBER_OF_EFFECTS
 4
OBSERVATION(S)
 16 14 15
WEIGHT(S)
 
EFFECTS: POSITIONS_IN_DATAFILE NUMBER_OF_LEVELS TYPE_OF_EFFECT  [EFFECT NESTED]
   1 1 1       53   cross
   5 5 5        2   cross
   6 6 6        1   cross
   10 0 10       1   cross
RANDOM_RESIDUAL VALUES
1 15 3
15 726 29.8509
3 29.8509 22.078
RANDOM_GROUP
 1
RANDOM_TYPE
add_animal
FILE
ex1.ped
(CO)VARIANCES
0.42857 -7.202 .6462
-7.202 484 15.198
.6462 15.198 3.9
OPTION category 3

data file: ex1.dat

53 6 0 7 2 1 0 6 1 0 10 1 0 290.0 36.5 1
52 6 0 7 2 1 0 6 1 0 10 1 0 317.8 43.5 2
 51  6  0  7  1  0  0  5  0  0  9  0  0 256.5  36.0 1
50 6 0 7 1 0 0 5 0 1 9 0 1 315.0 45.0 1
49 6 0 7 1 0 0 5 0 1 9 0 1 273.0 46.0 2
48 6 0 7 1 0 0 5 0 1 9 0 1 354.8 50.5 3
47 6 0 7 1 1 0 5 1 0 9 1 0 357.0 36.5 1
46 6 0 7 1 1 0 5 1 1 9 1 1 260.0 45.3 2
45 6 0 7 1 1 0 5 1 0 9 1 0 290.0 51.6 3
44 5 0 7 2 0 0 6 0 1 10 0 1 346.5 51.0 2
43 5 0 7 2 0 0 6 0 1 10 0 1 317.8 43.7 2
42 5 0 7 2 1 0 6 1 1 10 1 1 357.0 50.5 2
41 5 0 7 2 1 0 6 1 0 10 1 0 357.0 41.0 1
 40  5  0  7  1  0  0  5  0  0  9  0  0 344.0  48.0 3
39 5 0 7 1 0 0 5 0 1 9 0 1 346.5 52.0 1
38 5 0 7 1 0 0 5 0 1 9 0 1 328.0 38.5 1
37 5 0 7 1 0 0 5 0 1 9 0 1 285.0 48.8 2
36 5 0 7 1 0 0 5 0 1 9 0 1 396.0 42.5 1
35 5 0 7 1 1 0 5 1 0 9 1 0 304.5 43.5 1
34 5 0 7 1 1 0 5 1 1 9 1 1 346.5 40.5 1
33 4 0 7 2 1 0 6 1 1 10 1 1 333.3 44.5 1
 32  4  0  7  1  0  0  5  0  0  9  0  0 243.0  39.0 1
 31  4  0  7  1  0  0  5  0  0  9  0  0 344.0  51.0 2
30 4 0 7 1 0 0 5 0 1 9 0 1 328.0 47.0 2
29 3 0 7 2 0 0 6 0 1 10 0 1 320.0 46.0 1
 28  3  0  7  2  0  0  6  0  0 10  0  0 302.3  44.4 1
 27  3  0  7  2  0  0  6  0  0 10  0  0 266.0  32.5 1
26 3 0 7 2 1 0 6 1 0 10 1 0 328.0 42.7 1
25 3 0 7 2 1 0 6 1 1 10 1 1 300.0 36.0 1
24 3 0 7 1 1 0 5 1 1 9 1 1 341.0 41.6 1
23 2 0 7 2 0 0 6 0 1 10 0 1 273.0 49.0 1
22 2 0 7 2 0 0 6 0 1 10 0 1 300.0 44.5 1
21 2 0 7 1 0 0 5 0 1 9 0 1 315.0 42.0 1
20 2 0 7 1 0 0 5 0 1 9 0 1 307.5 47.0 2
 19  2  0  7  1  0  0  5  0  0  9  0  0 346.5  34.0 1
18 2 0 7 1 1 0 5 1 1 9 1 1 333.3 43.0 2
17 2 0 7 1 1 0 5 1 1 9 1 1 346.5 41.4 1
 16  1  0  7  2  0  0  6  0  0 10  0  0 346.5  39.0 1
15 1 0 7 2 1 0 6 1 0 10 1 0 374.0 40.5 1
14 1 0 7 2 1 0 6 1 0 10 1 0 336.0 46.0 1
 13  1  0  7  1  0  0  5  0  0  9  0  0 270.0  35.0 1
 12  1  0  7  1  0  0  5  0  0  9  0  0 310.0  42.0 1
 11  1  0  7  1  0  0  5  0  0  9  0  0 285.0  43.0 1
 10  1  0  7  1  0  0  5  0  0  9  0  0 374.0  40.0 1
9 1 0 7 1 1 0 5 1 0 9 1 0 354.8 41.5 1
8 1 0 7 1 1 0 5 1 1 9 1 1 304.5 37.5 1
7 1 0 7 1 1 0 5 1 1 9 1 1 328.0 41.0 1

pedigree file: ex1.ped

53 6 0
52 6 0
51 6 0
50 6 0
49 6 0
48 6 0
47 6 0
46 6 0
45 6 0
44 5 0
43 5 0
42 5 0
41 5 0
40 5 0
39 5 0
38 5 0
37 5 0
36 5 0
35 5 0
34 5 0
33 4 0
32 4 0
31 4 0
30 4 0
29 3 0
28 3 0
27 3 0
26 3 0
25 3 0
24 3 0
23 2 0
22 2 0
21 2 0
20 2 0
19 2 0
18 2 0
17 2 0
16 1 0
15 1 0
14 1 0
13 1 0
12 1 0
11 1 0
10 1 0
9 1 0
8 1 0
7 1 0
6 0 0
5 0 0
4 0 0
3 0 0
2 0 0
1 0 0

Output log:

 number of categories (numbered from 1)?
 name of parameter file?ex1.par
     CBLUP90IOD 1.0 by I. Misztal, 10/11/99
 Parameter file:             ex1.par
 Data file:                  ex1.dat
 Number of Traits             3
 Number of Effects            4
 Position of Observations     16 14 15
 Position of Weight (1)        0
 Value of Missing Trait/Observation           0
EFFECTS
 #  type                position (2)        levels   [positions for nested]
 1  cross-classified     1  1  1            53
 2  cross-classified     5  5  5             2
 3  cross-classified     6  6  6             1
 4  cross-classified    10  0 10             1
 Residual (co)variance Matrix
  1.0000      15.000      3.0000
  15.000      726.00      29.851
  3.0000      29.851      22.078
 Random Effect(s)   1
 Type of Random Effect:      additive animal
 Pedigree File:              ex1.ped
 trait   effect    (CO)VARIANCES
  1       1   0.42857     -7.2020     0.64620
  2       1   -7.2020      484.00      15.198
  3       1   0.64620      15.198      3.9000
 REMARKS
  (1) Weight position 0 means no weights utilized
  (2) Effect positions of 0 for some effects and traits means that such
      effects are missing for specified traits
 Data record length =   16
 number of rounds?
initial thresholds:   -0.5000   -0.0000
  0.42857      -7.2020      0.64620
  -7.2020       484.00       15.198
  0.64620       15.198       3.9000
 G inverse
   10.094      0.23098      -2.5726
  0.23098      0.76397E-02 -0.68043E-01
  -2.5726     -0.68043E-01  0.94782
 read   47  records
 eps =   1.545122445227030E-011   no. of iteration =   49
thresholds in round 1:   -0.47537   0.00000
 eps =   2.114189614579900E-011   no. of iteration =   46
thresholds in round 2:   -0.99853   0.00000
 eps =   3.195444694991311E-011   no. of iteration =   44
thresholds in round 3:   -1.21192   0.00000
 eps =   4.229633202398320E-011   no. of iteration =   44
thresholds in round 4:   -1.26689   0.00000
 solutions stored in file: "solutions"

parameter file: ex2.par

• Large simulated data set
• 3 traits, first one categorical (4 categories).

DATAFILE
ex2.dat
NUMBER_OF_TRAITS
 3
NUMBER_OF_EFFECTS
 2
OBSERVATION(S)
 3 4 5
WEIGHT(S)
 
EFFECTS: POSITIONS_IN_DATAFILE NUMBER_OF_LEVELS TYPE_OF_EFFECT  [EFFECT NESTED]
  2 2 2        50     cross
  1 1 1      1100     cross
RANDOM_RESIDUAL VALUES
     1.0000     7.7460     7.7460
     7.7460    1351.0      231.81
     7.7460    231.81      1369.0
RANDOM_GROUP
 2
RANDOM_TYPE
add_animal
FILE
ex2.ped
(CO)VARIANCES
     0.66667     5.16398     5.16398
     5.16398  1000.00000   200.00000
     5.16398   200.00000  1000.00000

Output log:

 number of categories (numbered from 1)?
 name of parameter file?ex2.par
     CBLUP90IOD 1.0 by I. Misztal, 10/11/99
 Parameter file:             ex2.par
 Data file:                  ex2.dat
 Number of Traits             3
 Number of Effects            2
 Position of Observations      3  4  5
 Position of Weight (1)        0
 Value of Missing Trait/Observation           0
EFFECTS
 #  type                position (2)        levels   [positions for nested]
 1  cross-classified     2  2  2            50
 2  cross-classified     1  1  1          1100
 Residual (co)variance Matrix
  1.0000      7.7460      7.7460
  7.7460      1351.0      231.81
  7.7460      231.81      1369.0
 Random Effect(s)   2
 Type of Random Effect:      additive animal
 Pedigree File:              ex2.ped
 trait   effect    (CO)VARIANCES
  1       2   0.66667      5.1640      5.1640
  2       2    5.1640      1000.0      200.00
  3       2    5.1640      200.00      1000.0
 REMARKS
  (1) Weight position 0 means no weights utilized
  (2) Effect positions of 0 for some effects and traits means that such
      effects are missing for specified traits
 Data record length =   5
 number of rounds?
initial thresholds:   -0.6667   -0.3333   -0.0000
  0.66667       5.1640       5.1640
   5.1640       1000.0       200.00
   5.1640       200.00       1000.0
 G inverse
   1.6071     -0.69160E-02 -0.69160E-02
 -0.69160E-02  0.10714E-02 -0.17857E-03
 -0.69160E-02 -0.17857E-03  0.10714E-02
 read   1000  records
 eps =   9.400106129966520E-011   no. of iteration =   41
thresholds in round 1:   -1.38764  -0.61188   0.00000
 eps =   9.044560960701230E-011   no. of iteration =   44
thresholds in round 2:   -1.86832  -0.90333   0.00000
 eps =   5.262946997597152E-011   no. of iteration =   46
thresholds in round 3:   -2.08856  -1.02189   0.00000
 eps =   8.666286752404070E-011   no. of iteration =   46
thresholds in round 4:   -2.15157  -1.05558   0.00000
 eps =   9.584502638477410E-011   no. of iteration =   46
thresholds in round 5:   -2.16738  -1.06370   0.00000
 solutions stored in file: "solutions"