blupf90으로 gblup model을 푸는 것은 다음 포스팅을 참고한다.
2020/12/29 - [Animal Breeding/BLUPF90] - blupf90으로 gblup model 풀기
blupf90으로 gblup model 풀기
blupf90은 ssGBLUP을 위하여 만든 프로그램이다. 그래서 gblup model을 다루기 위해서는 약간의 트릭이 필요하다. 그래서 renumf90으로 renumbering한 후 pregsf90을 실행하고 blupf90을 실행할 수 없다. pregsf90..
bhpark.tistory.com
위 포스팅에서 pregsf90 단계까지는 같은 자료를 가지고 똑같이 진행한다.
blupf90 실행을 위한 파라미터 파일
# BLUPF90 parameter file created by RENUMF90
DATAFILE
gblup_data.txt
NUMBER_OF_TRAITS
1
NUMBER_OF_EFFECTS
3
OBSERVATION(S)
6
WEIGHT(S)
EFFECTS: POSITIONS_IN_DATAFILE NUMBER_OF_LEVELS TYPE_OF_EFFECT[EFFECT NESTED]
4 1 cross
1 26 cross # residual polygenic effect
8 14 cross # new ID (renumbered only for genotyped animals)
RANDOM_RESIDUAL VALUES
245.00
RANDOM_GROUP
2
RANDOM_TYPE
add_animal
FILE
gblup_pedi.txt
(CO)VARIANCES
3.5241
RANDOM_GROUP
3
RANDOM_TYPE
user_file
FILE
Gi
(CO)VARIANCES
31.717
OPTION solv_method FSPAK
polygenic effect를 추가하여 NUMBER_OF_EFFECTS가 3이 되었다. 3개의 effects는 다음과 같다.
4 1 cross
1 26 cross # residual polygenic effect
8 14 cross # new ID (renumbered only for genotyped animals)
둘째 효과가 polygenic effect이다. 추가된 effect에 대한 설명은 다음과 같다.
RANDOM_GROUP
2
RANDOM_TYPE
add_animal
FILE
gblup_pedi.txt
(CO)VARIANCES
3.5241
나머지는 이전 분석과 같다.
blupf90을 실행한 화면
blupf90 실행 로그
blupf90_gblup_polygenic.par
BLUPF90 ver. 1.68
Parameter file: blupf90_gblup_polygenic.par
Data file: gblup_data.txt
Number of Traits 1
Number of Effects 3
Position of Observations 6
Position of Weight (1) 0
Value of Missing Trait/Observation 0
EFFECTS
# type position (2) levels [positions for nested]
1 cross-classified 4 1
2 cross-classified 1 26
3 cross-classified 8 14
Residual (co)variance Matrix
245.00
Random Effect(s) 2
Type of Random Effect: additive animal
Pedigree File: gblup_pedi.txt
trait effect (CO)VARIANCES
1 2 3.524
Random Effect(s) 3
Type of Random Effect: user defined from file
User File: Gi
trait effect (CO)VARIANCES
1 3 31.72
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
* The limited number of OpenMP threads = 4
* solving method (default=PCG):FSPAK
Data record length = 8
# equations = 41
G
3.5241
G
31.717
read 8 records in 0.1562500 s, 41
nonzeroes
read 26 additive pedigrees
g_usr_inv: read 105 elements
largest row, column, diagonal: 14 14 14
user defined matrix
36.3741 -27.9809 -8.2555 -7.2732 -16.9944 1.8651 1.0343 23.5797 2.9578 39.4427 15.7599 -17.6553 0.7099 5.1771
-27.9809 88.2709 31.3003 -7.9351 26.7420 -30.8381 -16.0748 -3.2541 -1.4220 -44.4016 -27.8617 -31.4539 38.4374 -6.0928
-8.2555 31.3003 17.5206 -13.8396 10.8256 -13.9611 10.9670 -4.3736 1.1504 -15.3606 -3.6702 -9.6102 12.3714 -1.1511
-7.2732 -7.9351 -13.8396 59.0298 1.1834 35.0358 -44.0422 13.6423 4.0692 8.9647 -16.8488 24.9842 -3.9326 4.3273
-16.9944 26.7420 10.8256 1.1834 16.5595 -3.7407 6.0548 -10.3559 1.6606 -23.7952 -5.4096 8.9787 8.4624 0.4650
1.8651 -30.8381 -13.9611 35.0358 -3.7407 33.9085 -9.4030 4.6108 4.1957 17.9323 1.6181 33.0855 -19.2868 5.1577
1.0343 -16.0748 10.9670 -44.0422 6.0548 -9.4030 76.5989 -30.6437 2.3328 -4.6811 31.9632 24.5245 -23.2509 0.4430
23.5797 -3.2541 -4.3736 13.6423 -10.3559 4.6108 -30.6437 38.8191 3.8658 31.0707 -11.6919 -26.2014 11.7456 3.0790
2.9578 -1.4220 1.1504 4.0692 1.6606 4.1957 2.3328 3.8658 3.5719 4.5230 2.2964 3.9327 1.0966 2.9069
39.4427 -44.4016 -15.3606 8.9647 -23.7952 17.9323 -4.6811 31.0707 4.5230 65.2412 12.4202 -9.8613 -22.5282 2.7339
15.7599 -27.8617 -3.6702 -16.8488 -5.4096 1.6181 31.9632 -11.6919 2.2964 12.4202 33.2898 12.7236 -8.6889 6.5557
-17.6553 -31.4539 -9.6102 24.9842 8.9787 33.0855 24.5245 -26.2014 3.9327 -9.8613 12.7236 65.5298 -29.4853 5.1203
0.7099 38.4374 12.3714 -3.9326 8.4624 -19.2868 -23.2509 11.7456 1.0966 -22.5282 -8.6889 -29.4853 46.4310 4.5049
5.1771 -6.0928 -1.1511 4.3273 0.4650 5.1577 0.4430 3.0790 2.9069 2.7339 6.5557 5.1203 4.5049 6.1332
finished peds in 0.1562500 s, 191 nonzeroes
solutions stored in file: "solutions"
blupf90 실행 결과 : solutions
trait/effect level solution
1 1 1 9.93629996
1 2 1 0.00000000
1 2 2 0.03710016
1 2 3 0.00000000
1 2 4 0.02506699
1 2 5 -0.02564345
1 2 6 -0.01365606
1 2 7 -0.00000000
1 2 8 -0.00000000
1 2 9 -0.03406764
1 2 10 -0.00000000
1 2 11 -0.00000000
1 2 12 -0.00000000
1 2 13 0.01065311
1 2 14 0.00054688
1 2 15 0.04292705
1 2 16 0.07711376
1 2 17 -0.01700165
1 2 18 -0.02021065
1 2 19 -0.01570340
1 2 20 -0.05188500
1 2 21 0.00000000
1 2 22 0.00027344
1 2 23 0.00027344
1 2 24 0.00027344
1 2 25 0.00027344
1 2 26 0.00027344
1 3 1 0.05511872
1 3 2 0.10731930
1 3 3 0.03187816
1 3 4 0.22808352
1 3 5 -0.45376632
1 3 6 -0.31731567
1 3 7 0.13243836
1 3 8 -0.20059690
1 3 9 0.02264487
1 3 10 0.10681153
1 3 11 -0.21392987
1 3 12 0.13204457
1 3 13 0.05330732
1 3 14 0.31846507
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