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Command used: wombat snappy2.par
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wombat snappy2.par
Script started on 2025-05-26 17:15:57+1000
 WOMBAT 26-05-2025 Maximum no. of threads to be used set to	      8

 Parameter file opened : "snappy2.par"
**RUNOP  --snap -v**
**COM  Example 14B: Bivariate SNP analysis**
**ANAL MUV 2**
  Analysis type = 2  "MUV 2"
  No. of traits =  2
**PEDS ../SimPed.dat**
  Pedigree file : "../SimPed.dat"
**DATA ../SimDataBiv.dat  GRP**
  Data file : "../SimDataBiv.dat"
**TRNOS  1  2**
**traitno  2**
  Data - column :      1  "traitno"	    2
**animal   0**
  Data - column :      2  "animal"	  -1
**kfix	   10**
  Data - column :      3  "kfix"	10
**mfix	   33**
  Data - column :      4  "mfix"	33
**lint	  999**
  Data - column :      5  "lint"       999
**snp**
  Data - column :      6  "snp"        -1
**age**
  Data - column :      7  "age"        -1
**NAMES  xxx  yyy**
	   1 xxx
	   2 yyy
**end**
**MODEL**
**FIX  kfix**
**FIX  mfix**
**COV  snp(1)**
**COV  age(2)**
**RAN animal  nrm**
**trait  xxx 1**
  Trait no.  1	"xxx"  Missing value  -123456789
**trait  yyy 2**
  Trait no.  2	"yyy"  Missing value  -123456789
**END MOD**
**VAR animal 2**
**30  -30  60**
**VAR residual 2**
**90  30   180**
**SPECIAL**
**COVZER snp(1) FIT**
 Covariable:"snp(1)" Treat values of 0 as: FIT
**SNPEFF snp(1)**
**END**

 End of parameter file reached :  32 lines read
 Data file appers to be sorted correctly
 No. of records in total			   =	       32
 No. of animal IDs in data			   =	       16
 Routine "REDUCEPEDS" to eliminate animals not connected to the data
 -> this may not account properly for genotyped animals & their ancestors
    do not use this routine if you have such information - perform equivalent
    calculations yourself prior to running WOMBAT & use run option --norped
"../SimPed.dat": skipping first  2 lines
 No. of animal IDs in data			   =	       16
 ***Time: begin idvec			      0 	  0 Used since last	    0.2 	0.2
 ***Time: end idvec			      0 	  0 Used since last	    0.0 	0.0
 Pedigree file					   = ../SimPed.dat
 Total no. of animal IDs found			   =	       26
 no. of NRM matrices		1	    1
 Pruned pedigree for random effect no.		 1
 Original no. of animals =	    26
 New no. of animals	 =	    26
 No. of "subjects" in data			   =	       16
 Maximum no. of records/individual =		   =		2	   399

 Inbreeding coefficients for random effect	   =		1 computed
 ... TIER's algorithm
 Covariance structure				   =	NRM
 No. of inbred animals				   =		0
 Average inbreeding coefficient 		   =  0.00000	  (in %)

 File "PrunedPedFile1.dat" written
 NRM Inverse no. :	     1	 "animal"
 No. of elements =	    66	 log determinant =  -11.0903548889591
    Zero out: 1st level  1  mfix	     1	 EqNo.	     10
    Zero out: 1st level  2  mfix	     2	 EqNo.	     16
 No. of "subjects" in data			   =	       16
 No. of combinations of records 		   =		1
 No. of effect codes/ind. (maxnr)		   =		6
 Parameters to be estimated & their starting values
    1  COVS Z 1 1	    90.000000	  F
    2  COVS Z 1 2	    30.000000	  F
    3  COVS Z 2 2	    180.00000	  F
    4  COVS A 1 1	    30.000000	  F
    5  COVS A 1 2	   -30.000000	  F
    6  COVS A 2 2	    60.000000	  F
 LSQ: END data - nrczhz =	   56
 Coefficient matrix fixed effects - rank =    16  no. of rows =    18
    Zero Out	       1  Row/Columnn No.	   10
    Zero Out	       2  Row/Columnn No.	   16
 END "lsqfixed"
 No. of equations in full rank submatrix =	    68
 nq,neqns,nnginv	   2	      70	  66  xx   7326.00000000000		7326  2147483646
 QTLSKIP	   1 eq no	     1
 QTLSKIP	   2 eq no	     2
 No. of equations in full rank submatrix =	    66
 adjact ivcol	    65934	65934
 Elements in MMM - after data		      323
 Elements in MMM - after RE    1	      493
 Start of "GENMMD": no. of rows 		   =	       66
 End of "GENMMD": no of subscripts		   =	      284
 No. of equations in full rank submatrix =	    68
 adjact ivcol	    65934	65934
 Elements in MMM - after data		      416
 Elements in MMM - after RE    1	      586
 adjact ivcol	    65934	65934
 Elements in MMM - after RHS		      632
 End of "SMBFCT": maxsub			   =	      302	    69
		  maxlnz			   =	      782
		  nnops 			   =  6476.00	  0.100000E+16
 END "eqnorders"
 MAXLNZ 	782
node size =	    2 n =	  19
node size =	    4 n =	   1
node size =	    6 n =	   1
node size =	   21 n =	   1
 "Super-nodes" :  No. of nodes			   =	       22
		  Max. size			   =	       21
 Start: factorisation of C  sys-time		   0.3
 End: factorisation of C  sys-time		 0.3
 Starting loop over SNPs ...
 File "SNPCounts.dat" found & opened
 Reading SNP allele counts with format: (16i1)
     21.1103	    -34.1390	     5.35456	     7.57249	     3.94249	    -4.50830	   SNPeffect1
     18.4090	    -35.3107	     5.93092	     8.38758	     3.10390	    -4.20987	   SNPeffect2
     14.1513	    -34.2044	     5.88339	     8.32037	     2.40531	    -4.11092	   SNPeffect3
     5.17559	    -14.1884	     6.87122	     9.71738	    0.753227	    -1.46011	   SNPeffect4
     5.17559	    -14.1884	     6.87122	     9.71738	    0.753227	    -1.46011	   SNPeffect5
     9.74797	    -18.0320	     7.26085	     10.2684	     1.34254	    -1.75606	   SNPeffect6
     6.12023	    -14.6315	     6.42189	     9.08193	    0.953026	    -1.61106	   SNPeffect7
     6.12023	    -14.6315	     6.42189	     9.08193	    0.953026	    -1.61106	   SNPeffect8
     4.06711	    -5.76998	     5.35494	     7.57303	    0.759505	   -0.761911	   SNPeffect9
     4.45945	    -7.08811	     4.62152	     6.53582	    0.964931	    -1.08450	   SNPeffect10

 "Snappy":	    10 cases for	    1  SNPs
 Output file for estimates: "SNPSolutions.dat"
 Total time used (secs): CPU =		 0  System =	       0
 Machine used = "didgeridoo"
 "WOMBAT" has finished !  26/05/2025


0.213u 0.209s 0:00.31 132.2%	0+0k 0+136io 0pf+0w

Script done on 2025-05-26 17:15:58+1000
