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Contents
1
Introduction
2
Availability
3
Getting started
3.1
Installation
3.1.1
Installation for
Linux
operating systems
3.1.2
Installation under
Windows
3.1.3
Running WOMBAT
3.1.4
Examples and testing
3.1.5
Compilation notes
3.1.6
Updates
3.2
Using the manual
3.3
Troubleshooting
3.4
Additional documentation
3.4.1
On-line version of the manual
3.4.2
Notes distributed with specific examples
3.4.3
Wiki pages
4
Parameter file
4.1
Overview
4.2
General rules
4.3
Run options
4.4
Comment line
4.5
Overriding default program limits
4.6
Analysis type
4.7
Pedigree file
4.8
Marker counts file
4.9
Data file
4.9.1
Simple
4.9.2
Compact
4.10
Model of analysis
4.10.1
Effects fitted
4.10.2
Fixed effects
4.10.3
Fixed covariables
4.10.4
Random effects
4.10.5
‘Subject’ identifier
4.10.6
‘Extra’ effects
4.10.7
Traits analysed
4.11
Covariance components
4.11.1
Residual covariances
4.11.2
Covariances for random effects
4.12
Additional functions of covariance components
4.13
Pooling estimates of covariance components
4.14
Dependencies among fixed effects
4.15
Random effects to be treated as fixed
4.16
Covariance components to be treated as fixed
4.17
Special information
4.17.1
Weighted analysis
4.17.2
Covariables that are zero
4.17.3
Animals that are clones
4.17.4
Standard errors for fixed and random effect solutions
4.17.5
GWAS from ssGBLUP: backsolving for marker effects
4.17.6
Repeated records
4.17.7
Fitting SNP effects
4.17.8
Sampling to approximate standard errors
4.17.9
Fitting “social” genetic effects
4.17.10
Fitting ‘explicit’ genetic groups
4.17.11
In core storage
4.17.12
Calculation of alternative outlier model statistics
4.17.13
Analyses using a Gaussian Kernel matrix
4.17.14
Correlations for random regression analyses
4.17.15
Genomic relationship matrices
4.17.16
Penalized estimation
5
Run options
5.1
Overview
5.2
Basic run options
5.2.1
Continuation run
5.2.2
Level of screen output
5.2.3
Set-up steps
5.2.4
Quality of starting values
5.2.5
Numerical settings
5.2.6
Intermediate results
5.2.7
Prediction only
5.2.8
Simulation only
5.2.9
Sampling to approximate standard errors
5.2.10
Matrix inversion only
5.2.11
Calculation of genomic relationships or
H
−
1
5.2.12
Quadratic approximation
5.2.13
Analyses of subsets of traits
5.2.14
Pooling estimates of covariance components from part analyses
5.2.15
Miscellaneous
5.3
Advanced run options
5.3.1
Ordering strategies
5.3.2
REML algorithms
5.3.3
Parameterisation
5.3.4
Matrix storage mode
5.3.5
Sparse matrix factorisation, auto-differentiation and inversion
5.3.6
Other
5.4
Parameter file name
6
Input files
6.1
Format
6.2
Data File
6.3
Pedigree File
6.4
Marker models: Allele counts
6.5
Parameter File
6.6
Other Files
6.6.1
General inverse
6.6.2
Basis function
6.6.3
GWAS: Allele counts
6.6.4
Results from part analyses
6.6.5
‘Utility’ files
6.6.6
File
SubSetsList
6.6.7
File(s)
Pen
*(
.dat
)
7
Output files
7.1
Main results files
7.1.1
File
SumPedigrees.out
7.1.2
File
SumModel.out
7.1.3
File
SumEstimates.out
7.1.4
File
BestSoFar.out
7.1.5
File
FixSolutions.out
7.1.6
File
SumSampleAI.out
7.2
Additional results
7.2.1
File
Residuals.dat
7.2.2
File(s)
RnSoln_
rname
.dat
7.2.3
File(s)
Curve_
cvname
(_
trname
).dat
7.2.4
File(s)
RanReg
name
.dat
7.2.5
Files
SimData
n
.dat
7.2.6
Files
EstimSubSet
n+
…
+m
.dat
7.2.7
Files
PDMatrix.dat
and
PDBestPoint
7.2.8
Files
PoolEstimates.out
and
PoolBestPoint
7.2.9
Files
MME
*
.dat
7.2.10
File
SNPSolutions.dat
and
SNPCovariances.dat
7.2.11
Files
Pen
*(
.dat
) and
ValidateLogLike.dat
7.2.12
File
CovSamples_
name
.dat
7.3
‘Utility’ files
7.3.1
File
ListOfCovs
7.3.2
File
RepeatedRecordsCounts
7.3.3
File
BestPoint
7.3.4
File
Iterates
7.3.5
File
OperationCounts
7.3.6
Files
AvInfoParms
and
AvinfoCovs
7.3.7
Files Covariable
.baf
7.3.8
File
LogL4Quapprox.dat
7.3.9
File
SubSetsList
7.4
Miscellaneous
7.4.1
File
ReducedPedFile.dat
7.4.2
Files
PrunedPedFile
n
.dat
7.4.3
File
WOMBAT.log
8
Work files
9
Examples
A
Technical details
A.1
Ordering strategies
A.2
Convergence citeria
A.3
Parameterisation
A.4
Approximation of sampling errors
A.4.1
Sampling covariances
A.4.2
Sampling errors of genetic parameters
A.5
Modification of the average information matrix
A.6
Iterative summation
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