wombat으로 multiple trait random regression model 풀기

wombat으로 multiple trait random regression model 풀기

 

R.A. Mrode가 제공한 예제

 

자료입력

 

1 4 4 1 4 17.0

1 4 4 2 38 18.6

1 4 4 3 72 24.0

1 4 4 4 106 20.0

1 4 4 5 140 20.0

1 4 4 6 174 15.6

1 4 4 7 208 16.0

1 4 4 8 242 13.0

1 4 4 9 276 8.2

1 4 4 10 310 8.0

2 4 4 1 4 11.0

2 4 4 2 38 12.4

2 4 4 3 72 16.0

2 4 4 4 106 13.3

2 4 4 5 140 14.0

2 4 4 6 174 10.6

2 4 4 7 208 10.8

2 4 4 8 242 9.6

2 4 4 9 276 6.6

2 4 4 10 310 5.9

1 5 5 1 4 23.0

1 5 5 2 38 21.0

1 5 5 3 72 18.0

1 5 5 4 106 17.0

1 5 5 5 140 16.2

1 5 5 6 174 14.0

1 5 5 7 208 14.2

1 5 5 8 242 13.4

1 5 5 9 276 11.8

1 5 5 10 310 11.4

2 5 5 1 4 17.0

2 5 5 2 38 13.8

2 5 5 3 72 13.0

2 5 5 4 106 16.1

2 5 5 5 140 10.8

2 5 5 6 174 9.5

2 5 5 7 208 10.2

2 5 5 8 242 8.9

2 5 5 9 276 8.8

2 5 5 10 310 9.4

1 6 6 6 4 10.4

1 6 6 7 38 12.3

1 6 6 8 72 13.2

1 6 6 9 106 11.6

1 6 6 10 140 8.4

2 6 6 6 4 12.0

2 6 6 7 38 9.8

2 6 6 8 72 16.0

2 6 6 9 106 19.8

2 6 6 10 140 5.6

1 7 7 4 4 22.8

1 7 7 5 38 22.4

1 7 7 6 72 21.4

1 7 7 7 106 18.8

1 7 7 8 140 18.3

1 7 7 9 174 16.2

1 7 7 10 208 15.0

2 7 7 4 4 19.2

2 7 7 5 38 11.0

2 7 7 6 72 24.6

2 7 7 7 106 10.3

2 7 7 8 140 12.8

2 7 7 9 174 7.4

2 7 7 10 208 10.0

1 8 8 1 4 22.2

1 8 8 2 38 20.0

1 8 8 3 72 21.0

1 8 8 4 106 23.0

1 8 8 5 140 16.8

1 8 8 6 174 11.0

1 8 8 7 208 13.0

1 8 8 8 242 17.0

1 8 8 9 276 13.0

1 8 8 10 310 12.6

2 8 8 1 4 25.0

2 8 8 2 38 18.2

2 8 8 3 72 16.6

2 8 8 4 106 21.0

2 8 8 5 140 17.0

2 8 8 6 174 9.8

2 8 8 7 208 10.3

2 8 8 8 242 12.0

2 8 8 9 276 14.0

2 8 8 10 310 11.6

 

형질번호, 개체, 개체(영구환경효과), HTD(herd-test-day), DIM(days in milk), test day yield

 

위 자료를 data.txt로 저장

 

혈통입력

 

1 0 0

2 0 0

3 0 0

4 1 2

5 3 2

6 1 5

7 3 4

8 1 7

 

개체, 아비, 어미

 

위 자료를 pedi.txt로 저장

 

파라미터 파일 작성

 

# run option - 육종가를 구할 때

# RnSoln_xxx.dat 출력 파일 확인

#RUNOP -d --solvit

 

# run option - 육종가와 SEP(standard error of prediction)

# reliability(r2) = 1- SEP^2 / sigma_a^2

# RnSoln_xxx.dat 출력 파일 확인

RUNOP -v --blup

 

# run option - 좋은 초기값으로 분산성분을 추정할 때,

#RUNOP -v --good

 

# run option - 나쁜 초기값일 때 분산성분을 추정할 때,

#RUNOP -v --bad

 

# 요약 출력파일에 출력할 내용

COMMENT Multiple traits Random Regression Model

 

# Analysis Type : multiple traits random regression model

ANALYSIS MRR 2

 

# 혈통 파일 이름

# SumPedigree.out 확인

PED pedi.txt

 

# 자료 파일 이름

DATA data.txt

 

TR1 traitno 2

TR1 animal

TR1 pe_ani 99

TR1 htd 10

TR1 dim 100

TR1 milk1

TR2 traitno 2

TR2 animal

TR2 pe_ani 99

TR2 htd 10

TR2 dim 100

TR2 milk2

END DATA

 

# Model of analysis

# SumModel.out 확인

# 고정효과의 차수, 5개를 구하고 싶으면 (4, LEG)라고 넣을 것

MODEL

FIX htd

COV dim(4,LEG)

RRC dim

RAN animal(3,LEG) NRM

RAN pe_ani(3,LEG)

TR milk1 1

TR milk2 2

END MODEL

 

# 분산 성분

VAR animal 6

4.3320 0.8292 -2.1556 0.6347 0.2988 0.0980

0.1668 -0.3993 0.1685 0.0644 0.0292

1.1178 -0.2659 -0.1685 0.0172

0.5201 0.1905 0.0033

0.1161 -0.0593

0.1954

 

VAR pe_ani 6

6.872 -0.254 -1.101 2.238 0.307 1.021

3.171 0.167 0.072 -0.059 0.040

2.457 0.391 -0.254 0.399

4.475 -0.184 -0.958

1.971 0.143

1.057

 

VAR residual 1 HOM

3.710 1.256

2.213

 

# SumModel.out 확인

# SumEstimates.out 확인

# SumPedigree.out 확인

# FixSolutions.out 확인

# RnSoln_xxx.dat 확인

 

위 파라미터 파일을 wombat.par로 저장

 

실행

 

위 세 파일을 한 폴더에 넣고 다음과 같이 실행

 

결과 확인

 

SumModel.out

 

======= Version 19-05-2012 ======================================= **KM** ====

 

Program WOMBAT : Summary of information from Set-up step

==============================================================================

 

Multiple traits Random Regression Model

 

Analysis type : "MRR 2"

Data file : "data.txt"

Pedigree file : "pedi.txt"

Parameter file : "wombat.par"

 

 

No. of traits = 2

nrec mean sdev min. max.

1 "milk1" 42 16.2095 4.45283 8.00000 24.0000

2 "milk2" 42 12.8976 4.57338 5.60000 25.0000

 

Numbers of individuals/records for pairs of traits

1 2

1 "milk1" 42 42

2 "milk2" 5 42

 

Covariables

1"milk1" nrec mean sdev min. max.

1 "dim(4,LEG)" 42 138.381 94.9724 4.00000 310.000

2"milk2" nrec mean sdev min. max.

1 "dim(4,LEG)" 42 138.381 94.9724 4.00000 310.000

 

Control variables in RR analysis

Trait no = 1

nrec mean sdev min. max.

1 "dim" 42 138.381 94.9724 4.00000 310.000

Trait no = 2

nrec mean sdev min. max.

1 "dim" 42 138.381 94.9724 4.00000 310.000

 

Fixed effects

1 "milk1" nlev

1 "htd" 10

2 "milk2" nlev

1 "htd" 10

 

Random effects nlev

1 "animal" 8 NRM

2 "pe_ani" 5 IDE

======== end of file ============================01-04-2014==========07:06====

 

SumPedigree.out

 

======= Version 19-05-2012 ======================================= **KM** ====

 

Program WOMBAT : Summary of Pedigree Information

==============================================================================

 

Multiple traits Random Regression Model

 

Analysis type : "MRR 2"

Data file : "data.txt"

Pedigree file : "pedi.txt"

Parameter file : "wombat.par"

 

 

No. of animal IDs in data file = = 5

No. of animal IDs in total = = 8

 

*****Pedigree Structure for random effect : 1 ****************************

Original no. of animals = 8

No. of animals after pruning = 8

... proportion (%) remaining = 100.0

 

No. of levels w/out records = 3

No. of levels with records = 5 100.0%

... 7-10 record(s) = 1 20.0%

... 11-20 record(s) = 4 80.0%

Minimum no. of records specified = 5

No. of animals with at least 5 records = 5 100.0%

No. of parents which have progeny which

have at least 5 records = 6

No. of animals with at least 5 records

themselves or on a parent = 5

No. of animals with at least 5 records

themselves, on a parent or sib(s) = 5 62.5%

... in the data = 5 100.0%

Minimum no. of records specified = 6

No. of animals with at least 6 records = 5 100.0%

No. of parents which have progeny which

have at least 6 records = 6

No. of animals with at least 6 records

themselves or on a parent = 5

No. of animals with at least 6 records

themselves, on a parent or sib(s) = 5 62.5%

... in the data = 5 100.0%

Minimum no. of records specified = 7

No. of animals with at least 7 records = 5 100.0%

No. of parents which have progeny which

have at least 7 records = 6

No. of animals with at least 7 records

themselves or on a parent = 5

No. of animals with at least 7 records

themselves, on a parent or sib(s) = 5 62.5%

... in the data = 5 100.0%

No. of animals w/out offspring = 2 25.0%

No. of animals with offspring = 6 75.0%

... and records = 3 37.5%

No. of animals with unknown sire = 3

No. of animals with unknown dam = 3

No. of animals with both parents unknown = 3

No. of animals with records =

... and unknown sire = 0

... and unknown dam = 0

... and both parents unknown = 0

No. of sires = 2

... with progeny in the data = 2

... with records & progeny in data = 0

No. of dams = 4

... with progeny in the data = 4

... with records & progeny in data = 3

 

No. of animals with known/unpruned grand-parents

... with paternal grandsire = 0

... with paternal granddam = 0

... with maternal grandsire = 3

... with maternal granddam = 3

random effect no. = 1 NRM

no. of elements in NRM/GIN inverse 23

log determinant = -3.4657359027997265

random effect no. = 2 IDE

no. of elements in NRM/GIN inverse 0

log determinant = 0.

======== end of file ============================01-04-2014==========07:06====

 

FixSolutions.out

 

======= Version 19-05-2012 ======================================= **KM** ======================================

 

Program WOMBAT : GLS solutions for fixed effects

================================================================================================================

 

Multiple traits Random Regression Model

 

 

Covariables for trait no. 1 "milk1"

Covariable Reg.coeff Solution S.Error

1 dim(4,LEG) 1 -0.541757 1.95170

1 dim(4,LEG) 2 -0.165203 1.26138

1 dim(4,LEG) 3 0.376545 0.552589

1 dim(4,LEG) 4 -0.427158 0.516205

 

Covariables for trait no. 2 "milk2"

Covariable Reg.coeff Solution S.Error

1 dim(4,LEG) 1 -2.34417 1.49057

1 dim(4,LEG) 2 0.359730 0.780042

1 dim(4,LEG) 3 1.68621 0.400349

1 dim(4,LEG) 4 -0.394062 0.398121

 

Fixed effects for trait no. 1 "milk1"

Effect Orig.code Level Solution S.Error SolSum=0 No.recs Eff.Mean

1 htd 1 1 5.94621 3.93619 5.28309 3 20.733

1 htd 2 2 3.33349 3.06359 2.67037 3 19.867

1 htd 3 3 4.23337 2.72167 3.57026 3 21.000

1 htd 4 4 3.88828 2.42573 3.22516 4 20.700

1 htd 5 5 1.92108 2.16828 1.25796 4 18.850

1 htd 6 6 -1.41825 1.90636 -2.08137 5 14.480

1 htd 7 7 -1.35487 1.73923 -2.01798 5 14.860

1 htd 8 8 -1.32249 1.81273 -1.98561 5 14.980

1 htd 9 9 -4.02428 2.04274 -4.68740 5 12.160

1 htd 10 10 -4.57136 2.52065 -5.23447 5 11.080

1 htd 0.663119

 

Fixed effects for trait no. 2 "milk2"

Effect Orig.code Level Solution S.Error SolSum=0 No.recs Eff.Mean

1 htd 1 1 5.42938 2.84643 5.43591 3 17.667

1 htd 2 2 -0.735292 2.24681 -0.728761 3 14.800

1 htd 3 3 -0.860115 1.96747 -0.853584 3 15.200

1 htd 4 4 2.47263 1.69483 2.47916 4 17.400

1 htd 5 5 -0.943094 1.47219 -0.936563 4 13.200

1 htd 6 6 0.918558 1.26066 0.925090 5 13.300

1 htd 7 7 -1.90479 1.13638 -1.89826 5 10.280

1 htd 8 8 -0.752519E-02 1.20733 -0.994028E-03 5 11.860

1 htd 9 9 -0.543310 1.38695 -0.536779 5 11.320

1 htd 10 10 -3.89175 1.76356 -3.88522 5 8.5000

1 htd -0.653116E-02

** marks effects which have been set to zero for the analysis

======== end of file ============================01-04-2014==========07:06======================================

 

 

RnSoln_animal.dat 확인

 

Run N Original ID Tr Solution St.Error Ignore Inbr %

1 1 1 -0.196776 1.94733 0.353 0.000

1 2 -0.146562E-01 0.384229 0.339

1 3 0.143123 0.987672 0.357

1 4 0.140527 0.703834 0.218

1 5 0.195215E-01 0.333516 0.205

1 6 0.800214E-01 0.429217 0.239

2 2 1 0.258226 2.02801 0.225 0.000

2 2 0.110326E-02 0.398815 0.216

2 3 -0.255912 1.02940 0.228

2 4 -0.255230 0.713975 0.141

2 5 0.522345E-02 0.337850 0.130

2 6 -0.271499 0.436691 0.155

3 3 1 -0.614504E-01 1.98550 0.300 0.000

3 2 0.135529E-01 0.391129 0.288

3 3 0.112789 1.00760 0.303

3 4 0.114703 0.709646 0.178

3 5 -0.247449E-01 0.335738 0.171

3 6 0.191478 0.433947 0.190

4 4 1 0.838214 1.90978 0.398 0.000

4 2 0.112536 0.377638 0.381

4 3 -0.556133 0.967518 0.403

4 4 -0.141468 0.698545 0.249

4 5 0.681289E-01 0.331679 0.229

4 6 -0.291614 0.424954 0.275

5 5 1 -0.450875 1.86615 0.443 0.000

5 2 -0.110881 0.369660 0.425

5 3 0.172264 0.944986 0.448

5 4 -0.241377 0.691125 0.286

5 5 -0.602938E-01 0.328839 0.262

5 6 -0.115635 0.419610 0.315

6 6 1 -0.635096 1.99106 0.291 0.000

6 2 -0.127046 0.391936 0.281

6 3 0.291232 1.01176 0.290

6 4 -0.107865 0.714216 0.139

6 5 -0.272408E-01 0.336294 0.161

6 6 -0.798458E-01 0.435540 0.171

7 7 1 0.876195 1.93000 0.374 0.000

7 2 0.194807 0.380886 0.361

7 3 -0.352708 0.980598 0.374

7 4 0.272435 0.707791 0.192

7 5 0.474801E-01 0.333171 0.210

7 6 0.217034 0.433722 0.193

8 8 1 -0.353285 1.96876 0.452 12.500

8 2 0.203832E-01 0.390255 0.434

8 3 0.404530 0.996689 0.458

8 4 0.488564 0.732497 0.288

8 5 0.412048E-02 0.348471 0.265

8 6 0.486463 0.444387 0.319

 

RnSoln_pe_ani.dat

 

Run N Original ID Tr Solution St.Error Ignore

1 4 1 -1.66346 1.88209 0.696

1 2 -0.510673 1.18415 0.747

1 3 -1.27590 1.13386 0.690

1 4 -1.60900 1.36011 0.766

1 5 0.486622 0.933154 0.747

1 6 -0.930672 0.698956 0.733

2 5 1 -0.904971 1.95881 0.665

2 2 0.183355 1.18948 0.744

2 3 1.01640 1.16207 0.671

2 4 -1.20859 1.38440 0.756

2 5 0.331221 0.940795 0.742

2 6 0.520342 0.708091 0.725

3 6 1 -2.18377 2.39304 0.408

3 2 0.815435 1.63017 0.402

3 3 -0.195353 1.39953 0.450

3 4 -0.479551 1.88597 0.453

3 5 0.278962E-01 1.28492 0.403

3 6 -0.681820 0.906311 0.472

4 7 1 3.85307 1.95379 0.667

4 2 -0.982746 1.47575 0.560

4 3 -0.255710 1.32607 0.533

4 4 0.734102 1.40583 0.747

4 5 0.143902 1.13408 0.589

4 6 1.02622 0.787347 0.643

5 8 1 0.899134 1.90398 0.687

5 2 0.494630 1.18539 0.746

5 3 0.710570 1.14207 0.685

5 4 2.56304 1.36739 0.763

5 5 -0.989641 0.935446 0.746

5 6 0.659297E-01 0.702258 0.730

 

결과 정리

 

animal genetic effect
number	tr1			tr2
	reg1	reg2	reg3	reg1	reg2	reg3
1	-0.1968	-0.0147	0.1431	0.1405	0.0195	0.0800
2	0.2582	0.0011	-0.2559	-0.2552	0.0052	-0.2715
3	-0.0615	0.0136	0.1128	0.1147	-0.0247	0.1915
4	0.8382	0.1125	-0.5561	-0.1415	0.0681	-0.2916
5	-0.4509	-0.1109	0.1723	-0.2414	-0.0603	-0.1156
6	-0.6351	-0.1270	0.2912	-0.1079	-0.0272	-0.0798
7	0.8762	0.1948	-0.3527	0.2724	0.0475	0.2170
8	-0.3533	0.0204	0.4045	0.4886	0.0041	0.4865

 

permanent environmental effect
number	tr1			tr2
	reg1	reg2	reg3	reg1	reg2	reg3
4	-1.6635	-0.5107	-1.2759	-1.6090	0.4866	-0.9307
5	-0.9050	0.1834	1.0164	-1.2086	0.3312	0.5203
6	-2.1838	0.8154	-0.1954	-0.4796	0.0279	-0.6818
7	3.8531	-0.9827	-0.2557	0.7341	0.1439	1.0262
8	0.8991	0.4946	0.7106	2.5630	-0.9896	0.0659

 

 

관련 파일

11_MTRR.zip