blupf90으로 single trait random regression model의 육종가 구하기
R. A. Mrode, Linear Models for the prediction of Animal Breeding Values, 2nd Edition. p144 Example 7.2
data
4 1 4 17.0
4 2 38 18.6
4 3 72 24.0
4 4 106 20.0
4 5 140 20.0
4 6 174 15.6
4 7 208 16.0
4 8 242 13.0
4 9 276 8.2
4 10 310 8.0
5 1 4 23.0
5 2 38 21.0
5 3 72 18.0
5 4 106 17.0
5 5 140 16.2
5 6 174 14.0
5 7 208 14.2
5 8 242 13.4
5 9 276 11.8
5 10 310 11.4
6 6 4 10.4
6 7 38 12.3
6 8 72 13.2
6 9 106 11.6
6 10 140 8.4
7 4 4 22.8
7 5 38 22.4
7 6 72 21.4
7 7 106 18.8
7 8 140 18.3
7 9 174 16.2
7 10 208 15.0
8 1 4 22.2
8 2 38 20.0
8 3 72 21.0
8 4 106 23.0
8 5 140 16.8
8 6 174 11.0
8 7 208 13.0
8 8 242 17.0
8 9 276 13.0
8 10 310 12.6
animal, htd(herd-test-day), dim(days-in-milk), test day fat yield
data.txt로 저장
renumf90(blupf90)은 random regression model을 위한 다항식(polynomial)을 자동으로 만들어 주지 않는다. 그래서 미리 dim에 대한 다항식을 만들어 주어야 한다. dim에 대한 다항식 만드는 방법에 대해서는 fixed regress model을 참고.
다음은 다항식을 data.txt의 왼쪽에 붙여 만든 data_2.txt의 내용이다.
0.707106781186548 -1.22474487139159 1.58113883008419 -1.87082869338697 2.12132034355964 4 1 4 17.0
0.707106781186548 -0.95257934441568 0.644167671515781 -0.0179640615277216 -0.620456293139911 4 2 38 18.6
0.707106781186548 -0.680413817439772 -0.0585606974105255 0.757056878668253 -0.775651197104036 4 3 72 24.0
0.707106781186548 -0.408248290463863 -0.52704627669473 0.762189467676173 0.0261891400439461 4 4 106 20.0
0.707106781186548 -0.136082763487954 -0.761289066336832 0.305389045971261 0.698700390555157 4 5 140 20.0
0.707106781186548 0.136082763487954 -0.761289066336832 -0.305389045971261 0.698700390555157 4 6 174 15.6
0.707106781186548 0.408248290463863 -0.52704627669473 -0.762189467676173 0.0261891400439465 4 7 208 16.0
0.707106781186548 0.680413817439772 -0.0585606974105255 -0.757056878668253 -0.775651197104036 4 8 242 13.0
0.707106781186548 0.95257934441568 0.64416767151578 0.0179640615277207 -0.620456293139912 4 9 276 8.2
0.707106781186548 1.22474487139159 1.58113883008419 1.87082869338697 2.12132034355964 4 10 310 8.0
0.707106781186548 -1.22474487139159 1.58113883008419 -1.87082869338697 2.12132034355964 5 1 4 23.0
0.707106781186548 -0.95257934441568 0.644167671515781 -0.0179640615277216 -0.620456293139911 5 2 38 21.0
0.707106781186548 -0.680413817439772 -0.0585606974105255 0.757056878668253 -0.775651197104036 5 3 72 18.0
0.707106781186548 -0.408248290463863 -0.52704627669473 0.762189467676173 0.0261891400439461 5 4 106 17.0
0.707106781186548 -0.136082763487954 -0.761289066336832 0.305389045971261 0.698700390555157 5 5 140 16.2
0.707106781186548 0.136082763487954 -0.761289066336832 -0.305389045971261 0.698700390555157 5 6 174 14.0
0.707106781186548 0.408248290463863 -0.52704627669473 -0.762189467676173 0.0261891400439465 5 7 208 14.2
0.707106781186548 0.680413817439772 -0.0585606974105255 -0.757056878668253 -0.775651197104036 5 8 242 13.4
0.707106781186548 0.95257934441568 0.64416767151578 0.0179640615277207 -0.620456293139912 5 9 276 11.8
0.707106781186548 1.22474487139159 1.58113883008419 1.87082869338697 2.12132034355964 5 10 310 11.4
0.707106781186548 -1.22474487139159 1.58113883008419 -1.87082869338697 2.12132034355964 6 6 4 10.4
0.707106781186548 -0.95257934441568 0.644167671515781 -0.0179640615277216 -0.620456293139911 6 7 38 12.3
0.707106781186548 -0.680413817439772 -0.0585606974105255 0.757056878668253 -0.775651197104036 6 8 72 13.2
0.707106781186548 -0.408248290463863 -0.52704627669473 0.762189467676173 0.0261891400439461 6 9 106 11.6
0.707106781186548 -0.136082763487954 -0.761289066336832 0.305389045971261 0.698700390555157 6 10 140 8.4
0.707106781186548 -1.22474487139159 1.58113883008419 -1.87082869338697 2.12132034355964 7 4 4 22.8
0.707106781186548 -0.95257934441568 0.644167671515781 -0.0179640615277216 -0.620456293139911 7 5 38 22.4
0.707106781186548 -0.680413817439772 -0.0585606974105255 0.757056878668253 -0.775651197104036 7 6 72 21.4
0.707106781186548 -0.408248290463863 -0.52704627669473 0.762189467676173 0.0261891400439461 7 7 106 18.8
0.707106781186548 -0.136082763487954 -0.761289066336832 0.305389045971261 0.698700390555157 7 8 140 18.3
0.707106781186548 0.136082763487954 -0.761289066336832 -0.305389045971261 0.698700390555157 7 9 174 16.2
0.707106781186548 0.408248290463863 -0.52704627669473 -0.762189467676173 0.0261891400439465 7 10 208 15.0
0.707106781186548 -1.22474487139159 1.58113883008419 -1.87082869338697 2.12132034355964 8 1 4 22.2
0.707106781186548 -0.95257934441568 0.644167671515781 -0.0179640615277216 -0.620456293139911 8 2 38 20.0
0.707106781186548 -0.680413817439772 -0.0585606974105255 0.757056878668253 -0.775651197104036 8 3 72 21.0
0.707106781186548 -0.408248290463863 -0.52704627669473 0.762189467676173 0.0261891400439461 8 4 106 23.0
0.707106781186548 -0.136082763487954 -0.761289066336832 0.305389045971261 0.698700390555157 8 5 140 16.8
0.707106781186548 0.136082763487954 -0.761289066336832 -0.305389045971261 0.698700390555157 8 6 174 11.0
0.707106781186548 0.408248290463863 -0.52704627669473 -0.762189467676173 0.0261891400439465 8 7 208 13.0
0.707106781186548 0.680413817439772 -0.0585606974105255 -0.757056878668253 -0.775651197104036 8 8 242 17.0
0.707106781186548 0.95257934441568 0.64416767151578 0.0179640615277207 -0.620456293139912 8 9 276 13.0
0.707106781186548 1.22474487139159 1.58113883008419 1.87082869338697 2.12132034355964 8 10 310 12.6
pedigree
1 0 0
2 0 0
3 0 0
4 1 2
5 3 2
6 1 5
7 3 4
8 1 7
pedi.txt로 저장
renumf90을 위한 parameter 파일 작성
# Parameter file for program renf90; it is translated to parameter
# file for BLUPF90 family programs.
DATAFILE
data_2.txt
TRAITS
9
FIELDS_PASSED TO OUTPUT
WEIGHT(S)
RESIDUAL_VARIANCE
3.71
EFFECT
7 cross numer
EFFECT
1 cov
EFFECT
2 cov
EFFECT
3 cov
EFFECT
4 cov
EFFECT
5 cov
EFFECT
6 cross alpha
RANDOM
animal
OPTIONAL
pe
FILE
pedi.txt
FILE_POS
1 2 3
PED_DEPTH
0
RANDOM_REGRESSION
data
RR_POSITION
1 2 3
(CO)VARIANCES
3.297 0.594 -1.381
0.594 0.921 -0.289
-1.381 -0.289 1.005
(CO)VARIANCES_PE
6.872 -0.254 -1.101
-0.254 3.171 0.167
-1.101 0.167 2.457
설명
DATAFILE
data_2.txt
자료 파일 이름
TRAITS
9
자료 파일에서 관측치의 위치(컬럼)
FIELDS_PASSED TO OUTPUT
WEIGHT(S)
RESIDUAL_VARIANCE
3.71
잔차 분산
EFFECT
7 cross numer
7 컬럼(HTD:herd-test-day)이 고정효과로 쓰임
셋째 컬럼이 고정효과로 쓰임
EFFECT
1 cov
EFFECT
2 cov
EFFECT
3 cov
EFFECT
4 cov
EFFECT
5 cov
첫째 컬럼에서 다섯째 컬럼이 회귀 변수
EFFECT
6 cross alpha
6째 컬럼이 분류 효과(숫자로 되어 있어도 alpha로 하기 바란다. numer로 하면 제대로 처리가 되지 않는다.)
RANDOM
animal
임의 개체 효과
OPTIONAL
pe
개체의 자료가 중복됨에 따라 영구 환경 효과 추가
FILE
pedi.txt
혈통 파일 이름
FILE_POS
1 2 3
혈통 파일은 animal, sire, dam
PED_DEPTH
0
끝까지 혈통 추적
RANDOM_REGRESSION
data
임의 회귀 변수임을 선언(회귀 변수가 이 효과에 nested 된다는 의미)
RR_POSITION
1 2 3
개체 효과에 nested 되는 회귀 변수 지정(order = 3)
(CO)VARIANCES
3.297 0.594 -1.381
0.594 0.921 -0.289
-1.381 -0.289 1.005
개체 효과 분산-공분산 행렬
(CO)VARIANCES_PE
6.872 -0.254 -1.101
-0.254 3.171 0.167
-1.101 0.167 2.457
영구 환경 효과의 분산
실행 화면
생성된 파일
renf90.tables
Effect group 1 of column 1 with 10 levels, effect # 1
Value # consecutive number
1 3 1
2 3 2
3 3 3
4 4 4
5 4 5
6 5 6
7 5 7
8 5 8
9 5 9
10 5 10
고정효과 : 원래 번호, 개수, 새로운 번호
renf90.dat
17.0 0.707106781186548 -1.22474487139159 1.58113883008419 1 0.707106781186548 -1.22474487139159 1.58113883008419 -1.87082869338697 2.12132034355964 4
18.6 0.707106781186548 -0.95257934441568 0.644167671515781 2 0.707106781186548 -0.95257934441568 0.644167671515781 -0.0179640615277216 -0.620456293139911 4
24.0 0.707106781186548 -0.680413817439772 -0.0585606974105255 3 0.707106781186548 -0.680413817439772 -0.0585606974105255 0.757056878668253 -0.775651197104036 4
20.0 0.707106781186548 -0.408248290463863 -0.52704627669473 4 0.707106781186548 -0.408248290463863 -0.52704627669473 0.762189467676173 0.0261891400439461 4
20.0 0.707106781186548 -0.136082763487954 -0.761289066336832 5 0.707106781186548 -0.136082763487954 -0.761289066336832 0.305389045971261 0.698700390555157 4
15.6 0.707106781186548 0.136082763487954 -0.761289066336832 6 0.707106781186548 0.136082763487954 -0.761289066336832 -0.305389045971261 0.698700390555157 4
16.0 0.707106781186548 0.408248290463863 -0.52704627669473 7 0.707106781186548 0.408248290463863 -0.52704627669473 -0.762189467676173 0.0261891400439465 4
13.0 0.707106781186548 0.680413817439772 -0.0585606974105255 8 0.707106781186548 0.680413817439772 -0.0585606974105255 -0.757056878668253 -0.775651197104036 4
8.2 0.707106781186548 0.95257934441568 0.64416767151578 9 0.707106781186548 0.95257934441568 0.64416767151578 0.0179640615277207 -0.620456293139912 4
8.0 0.707106781186548 1.22474487139159 1.58113883008419 10 0.707106781186548 1.22474487139159 1.58113883008419 1.87082869338697 2.12132034355964 4
23.0 0.707106781186548 -1.22474487139159 1.58113883008419 1 0.707106781186548 -1.22474487139159 1.58113883008419 -1.87082869338697 2.12132034355964 1
21.0 0.707106781186548 -0.95257934441568 0.644167671515781 2 0.707106781186548 -0.95257934441568 0.644167671515781 -0.0179640615277216 -0.620456293139911 1
18.0 0.707106781186548 -0.680413817439772 -0.0585606974105255 3 0.707106781186548 -0.680413817439772 -0.0585606974105255 0.757056878668253 -0.775651197104036 1
17.0 0.707106781186548 -0.408248290463863 -0.52704627669473 4 0.707106781186548 -0.408248290463863 -0.52704627669473 0.762189467676173 0.0261891400439461 1
16.2 0.707106781186548 -0.136082763487954 -0.761289066336832 5 0.707106781186548 -0.136082763487954 -0.761289066336832 0.305389045971261 0.698700390555157 1
14.0 0.707106781186548 0.136082763487954 -0.761289066336832 6 0.707106781186548 0.136082763487954 -0.761289066336832 -0.305389045971261 0.698700390555157 1
14.2 0.707106781186548 0.408248290463863 -0.52704627669473 7 0.707106781186548 0.408248290463863 -0.52704627669473 -0.762189467676173 0.0261891400439465 1
13.4 0.707106781186548 0.680413817439772 -0.0585606974105255 8 0.707106781186548 0.680413817439772 -0.0585606974105255 -0.757056878668253 -0.775651197104036 1
11.8 0.707106781186548 0.95257934441568 0.64416767151578 9 0.707106781186548 0.95257934441568 0.64416767151578 0.0179640615277207 -0.620456293139912 1
11.4 0.707106781186548 1.22474487139159 1.58113883008419 10 0.707106781186548 1.22474487139159 1.58113883008419 1.87082869338697 2.12132034355964 1
10.4 0.707106781186548 -1.22474487139159 1.58113883008419 6 0.707106781186548 -1.22474487139159 1.58113883008419 -1.87082869338697 2.12132034355964 3
12.3 0.707106781186548 -0.95257934441568 0.644167671515781 7 0.707106781186548 -0.95257934441568 0.644167671515781 -0.0179640615277216 -0.620456293139911 3
13.2 0.707106781186548 -0.680413817439772 -0.0585606974105255 8 0.707106781186548 -0.680413817439772 -0.0585606974105255 0.757056878668253 -0.775651197104036 3
11.6 0.707106781186548 -0.408248290463863 -0.52704627669473 9 0.707106781186548 -0.408248290463863 -0.52704627669473 0.762189467676173 0.0261891400439461 3
8.4 0.707106781186548 -0.136082763487954 -0.761289066336832 10 0.707106781186548 -0.136082763487954 -0.761289066336832 0.305389045971261 0.698700390555157 3
22.8 0.707106781186548 -1.22474487139159 1.58113883008419 4 0.707106781186548 -1.22474487139159 1.58113883008419 -1.87082869338697 2.12132034355964 5
22.4 0.707106781186548 -0.95257934441568 0.644167671515781 5 0.707106781186548 -0.95257934441568 0.644167671515781 -0.0179640615277216 -0.620456293139911 5
21.4 0.707106781186548 -0.680413817439772 -0.0585606974105255 6 0.707106781186548 -0.680413817439772 -0.0585606974105255 0.757056878668253 -0.775651197104036 5
18.8 0.707106781186548 -0.408248290463863 -0.52704627669473 7 0.707106781186548 -0.408248290463863 -0.52704627669473 0.762189467676173 0.0261891400439461 5
18.3 0.707106781186548 -0.136082763487954 -0.761289066336832 8 0.707106781186548 -0.136082763487954 -0.761289066336832 0.305389045971261 0.698700390555157 5
16.2 0.707106781186548 0.136082763487954 -0.761289066336832 9 0.707106781186548 0.136082763487954 -0.761289066336832 -0.305389045971261 0.698700390555157 5
15.0 0.707106781186548 0.408248290463863 -0.52704627669473 10 0.707106781186548 0.408248290463863 -0.52704627669473 -0.762189467676173 0.0261891400439465 5
22.2 0.707106781186548 -1.22474487139159 1.58113883008419 1 0.707106781186548 -1.22474487139159 1.58113883008419 -1.87082869338697 2.12132034355964 2
20.0 0.707106781186548 -0.95257934441568 0.644167671515781 2 0.707106781186548 -0.95257934441568 0.644167671515781 -0.0179640615277216 -0.620456293139911 2
21.0 0.707106781186548 -0.680413817439772 -0.0585606974105255 3 0.707106781186548 -0.680413817439772 -0.0585606974105255 0.757056878668253 -0.775651197104036 2
23.0 0.707106781186548 -0.408248290463863 -0.52704627669473 4 0.707106781186548 -0.408248290463863 -0.52704627669473 0.762189467676173 0.0261891400439461 2
16.8 0.707106781186548 -0.136082763487954 -0.761289066336832 5 0.707106781186548 -0.136082763487954 -0.761289066336832 0.305389045971261 0.698700390555157 2
11.0 0.707106781186548 0.136082763487954 -0.761289066336832 6 0.707106781186548 0.136082763487954 -0.761289066336832 -0.305389045971261 0.698700390555157 2
13.0 0.707106781186548 0.408248290463863 -0.52704627669473 7 0.707106781186548 0.408248290463863 -0.52704627669473 -0.762189467676173 0.0261891400439465 2
17.0 0.707106781186548 0.680413817439772 -0.0585606974105255 8 0.707106781186548 0.680413817439772 -0.0585606974105255 -0.757056878668253 -0.775651197104036 2
13.0 0.707106781186548 0.95257934441568 0.64416767151578 9 0.707106781186548 0.95257934441568 0.64416767151578 0.0179640615277207 -0.620456293139912 2
12.6 0.707106781186548 1.22474487139159 1.58113883008419 10 0.707106781186548 1.22474487139159 1.58113883008419 1.87082869338697 2.12132034355964 2
trait1, 임의회귀 개체효과1 - 임의회귀 개체효과3, HTD, 고정회귀변수1 – 고정회귀변수3, 개체효과
renadd03.ped
1 8 7 1 0 2 10 0 1 5
8 0 0 3 0 0 0 2 0 3
2 6 5 1 0 2 10 0 0 8
6 0 0 3 0 0 0 3 0 1
3 6 1 1 0 2 5 0 0 6
4 6 7 1 0 2 10 0 1 4
7 0 0 3 0 0 0 0 2 2
5 8 4 1 0 2 7 0 1 7
renumbered 된 혈통. 자세한 설명은 single trait animal model 참조
renf90.par
# BLUPF90 parameter file created by RENF90
DATAFILE
renf90.dat
NUMBER_OF_TRAITS
1
NUMBER_OF_EFFECTS
12
OBSERVATION(S)
1
WEIGHT(S)
EFFECTS: POSITIONS_IN_DATAFILE NUMBER_OF_LEVELS TYPE_OF_EFFECT[EFFECT NESTED]
5 10 cross
6 1 cov
7 1 cov
8 1 cov
9 1 cov
10 1 cov
2 8 cov 11
3 8 cov 11
4 8 cov 11
2 8 cov 11
3 8 cov 11
4 8 cov 11
RANDOM_RESIDUAL VALUES
3.710000
RANDOM_GROUP
7 8 9
RANDOM_TYPE
add_animal
FILE
renadd07.ped
(CO)VARIANCES
3.297000 0.5940000 -1.381000
0.5940000 0.9210000 -0.2890000
-1.381000 -0.2890000 1.005000
RANDOM_GROUP
10 11 12
RANDOM_TYPE
diagonal
FILE
(CO)VARIANCES
6.872000 -0.2540000 -1.101000
-0.2540000 3.171000 0.1670000
-1.101000 0.1670000 2.457000
설명
DATAFILE
renf90.dat
자료 파일의 이름
NUMBER_OF_TRAITS
1
형질의 수
NUMBER_OF_EFFECTS
12
효과의 수(htd, dim1 ~ dim5, 개체효과1 ~ 개체효과3, 영구환경효과1 ~ 영구환경효과3)
OBSERVATION(S)
1
관측치의 위치
WEIGHT(S)
EFFECTS: POSITIONS_IN_DATAFILE NUMBER_OF_LEVELS TYPE_OF_EFFECT[EFFECT NESTED]
5 10 cross
6 1 cov
7 1 cov
8 1 cov
9 1 cov
10 1 cov
2 8 cov 11
3 8 cov 11
4 8 cov 11
2 8 cov 11
3 8 cov 11
4 8 cov 11
다섯째 컬럼이 효과. 레벨 개수는 10, 분류 효과
여섯째 컬럼에서 열째 컬럼이 연속 변수 효과.
둘째 컬럼에서 넷째 컬럼이 연속 변수 효과. 개체 효과와 영구 환경 효과로 쓰일 것이므로 두 번 쓰임
RANDOM_RESIDUAL VALUES
3.710000
잔차 효과의 분산
RANDOM_GROUP
7 8 9
효과 중 일곱째에서 아홉째 효과가 임의 효과 그룹
RANDOM_TYPE
add_animal
additive genetic animal effect
FILE
renadd07.ped
혈통 파일의 이름
(CO)VARIANCES
3.297000 0.5940000 -1.381000
0.5940000 0.9210000 -0.2890000
-1.381000 -0.2890000 1.005000
개체 효과의 분산-공분산 행렬
RANDOM_GROUP
10 11 12
효과 중 열째 효과에서 열두째가 임의 효과
RANDOM_TYPE
diagonal
영구 환경 효과이므로 diagonal
FILE
파일 지정하지 않음
(CO)VARIANCES
6.872000 -0.2540000 -1.101000
-0.2540000 3.171000 0.1670000
-1.101000 0.1670000 2.457000
영구 환경 효과의 분산-공분산 행렬
blupf90 실행 화면
solutions 결과 파일
trait/effect level solution
1 1 1 13.75528202
1 1 2 11.25996236
1 1 3 12.22924685
1 1 4 11.91212085
1 1 5 9.98521457
1 1 6 6.67922242
1 1 7 6.77765335
1 1 8 6.84095218
1 1 9 4.17359916
1 1 10 3.66918671
1 2 1 11.44926728
1 3 1 -0.62539157
1 4 1 -0.13457792
1 5 1 0.34791064
1 6 1 -0.42175200
1 7 1 -0.45375131
1 7 2 0.22083236
1 7 3 -0.54855595
1 7 4 0.34454297
1 7 5 0.85183658
1 7 6 -0.05832534
1 7 7 -0.07283681
1 7 8 0.13115737
1 8 1 -0.05201238
1 8 2 0.01271886
1 8 3 0.07301430
1 8 4 0.00627371
1 8 5 -0.00947069
1 8 6 0.05520153
1 8 7 -0.03051505
1 8 8 -0.02466526
1 9 1 0.27980869
1 9 2 -0.01743426
1 9 3 0.19456422
1 9 4 -0.31640867
1 9 5 -0.31309002
1 9 6 -0.04417675
1 9 7 -0.02437567
1 9 8 0.06853337
1 10 1 -0.77612671
1 10 2 -0.10131195
1 10 3 -1.99267893
1 10 4 -0.64859053
1 10 5 3.51874830
1 10 6 0.00000000
1 10 7 0.00000000
1 10 8 0.00000000
1 11 1 0.13701010
1 11 2 0.28888733
1 11 3 0.98510143
1 11 4 -0.36003168
1 11 5 -1.05097953
1 11 6 0.00000000
1 11 7 0.00000000
1 11 8 0.00000000
1 12 1 0.96883255
1 12 2 0.97706292
1 12 3 -0.06930251
1 12 4 -1.47182321
1 12 5 -0.40471878
1 12 6 0.00000000
1 12 7 0.00000000
1 12 8 0.00000000
결과 정리
HTD | |
level | solution |
1 | 13.7553 |
2 | 11.2600 |
3 | 12.2292 |
4 | 11.9121 |
5 | 9.9852 |
6 | 6.6792 |
7 | 6.7777 |
8 | 6.8410 |
9 | 4.1736 |
10 | 3.6692 |
fixed regression | |
level | solution |
1 | 11.4493 |
1 | -0.6254 |
1 | -0.1346 |
1 | 0.3479 |
1 | -0.4218 |
animal - regression coefficient | ||||
level | solution1 | solution2 | solution3 | original ID |
1 | -0.4538 | -0.0520 | 0.2798 | 5 |
2 | 0.2208 | 0.0127 | -0.0174 | 8 |
3 | -0.5486 | 0.0730 | 0.1946 | 6 |
4 | 0.3445 | 0.0063 | -0.3164 | 4 |
5 | 0.8518 | -0.0095 | -0.3131 | 7 |
6 | -0.0583 | 0.0552 | -0.0442 | 1 |
7 | -0.0728 | -0.0305 | -0.0244 | 2 |
8 | 0.1312 | -0.0247 | 0.0685 | 3 |
permanent environment effects - regression coefficient | ||||
level | solution1 | solution2 | solution3 | original ID |
1 | -0.7761 | 0.1370 | 0.9688 | 5 |
2 | -0.1013 | 0.2889 | 0.9771 | 8 |
3 | -1.9927 | 0.9851 | -0.0693 | 6 |
4 | -0.6486 | -0.3600 | -1.4718 | 4 |
5 | 3.5187 | -1.0510 | -0.4047 | 7 |
6 |
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| 1 |
7 |
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| 2 |
8 |
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| 3 |
관련 파일
10_strrm.zip'Animal Breeding > BLUPF90' 카테고리의 다른 글
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