Dear Erwin,
I have looked at your sample job. The groups analysis as
you had it was not working. It is because I assumed there would be more
than 1 genetic group. If you change !GROUPS 1 to !GROUPS 2,
it will work. I have changed ASREML to allow a single genetic group
[in the next release].
{{However, I have recently upgraded my Fortran compiler on the SUN
and the graphics library is now not working so I am unsure when I can
produce a new version for release.}}
So, I now get [from the group.sln file\
mu 1 0.000 0.000
animal C 4.700 0.4000
animal A 4.369 0.5615
animal B 5.031 0.5615
animal 1 4.096 0.5224
animal 2 4.944 0.5224
animal 3 4.520 0.5224
animal 4 4.732 0.5224
animal 5 3.884 0.5224
animal 6 4.499 0.5224
animal 7 5.347 0.5224
animal 8 4.923 0.5224
animal 9 5.347 0.5224
animal 10 4.711 0.5224
Residual 1 -0.5958 4.096
Residual 2 0.5562 4.944
Residual 3 -0.1980E-01 4.520
Residual 4 0.2682 4.732
Residual 5 -0.8838 3.884
Residual 6 -0.4986 4.499
Residual 7 0.6534 5.347
Residual 8 0.7740E-01 4.923
Residual 9 0.6534 5.347
Residual 10 -0.2106 4.711
Compared with [nogroups.sln]
mu 1 4.700 0.4000
animal A -0.3312 0.6483
animal B 0.3312 0.6483
animal 1 -0.6041 0.5700
animal 2 0.2438 0.5700
animal 3 -0.1802 0.5700
animal 4 0.3178E-01 0.5700
animal 5 -0.8161 0.5700
animal 6 -0.2014 0.5700
animal 7 0.6465 0.5700
animal 8 0.2226 0.5700
animal 9 0.6465 0.5700
animal 10 0.1061E-01 0.5700
Residual 1 -0.5959 4.096
Residual 2 0.5562 4.944
Residual 3 -0.1981E-01 4.520
Residual 4 0.2682 4.732
Residual 5 -0.8839 3.884
Residual 6 -0.4986 4.499
Residual 7 0.6535 5.347
Residual 8 0.7741E-01 4.923
Residual 9 0.6535 5.347
Residual 10 -0.2106 4.711
These results are entirely consistent and do not show the problem
that erwin reported (below).
[Of course I had different results before I fixed the group count
but then the solutions were obviously different converging to a
very different solution.]
It is important to specify the number of genetic groups in the !GROUPS
qualifier [apparently an over estimate is no problem]. Maybe
you had an underestimate in your example. If so, I expect
ASREML might give a warning message.
Arthur
~
~
>
> Dear colleagues,
>
> I tried to fit some large animals models including genetic groups and
> compared them with models without genetic groups. I carefully checked that
> all unknown animals in the pedigree file were assigned to a genetic group.
>
> In the models with genetic groups I found very high SE for estimates for
> the effects of animal (derived from *.sln files) compared to the estimated
> genetic variance. As an example, I found a genetic variance of 0.66 whereas
> the SE of
> an animal was 1.472, which seems to be much too high.
>
> What might be wrong here ?
>
> To test the genetic groups I compared the results of a very small example
> (10 animals, two sires, unknown dams) with and without genetic groups
> (group.as vs. nogroup.as, see below). Also here I ended with different
> results.
> In the no-group version I found an estimate for A of -0.3105 (SE 0.6207)
> whereas it was -0.500 (SE 1.905) in the version with genetic groups. I
> expected the same results when all unknown animals are assigned to the same
> genetic group.
> I am not quite sure if the differences of these small exemples are caused by
> the size of the data or by mistakes in the *.as files.
>
> Best regards,
>
> Erwin Koenen
>
>
>
> NOGROUP.DAT / GROUP.DAT
>
> 1 3.5
> 2 5.5
> 3 4.5
> 4 5.0
> 5 3.0
> 6 4.0
> 7 6.0
> 8 5.0
> 9 6.0
> 10 4.5
>
> NOGROUP.PED
> A 0 0
> B 0 0
> 1 A 0
> 2 A 0
> 3 A 0
> 4 A 0
> 5 A 0
> 6 B 0
> 7 B 0
> 8 B 0
> 9 B 0
> 10 B 0
>
> GROUP.PED
> C 0 0
> A C C
> B C C
> 1 A C
> 2 A C
> 3 A C
> 4 A C
> 5 A C
> 6 B C
> 7 B C
> 8 B C
> 9 B C
> 10 B C
>
> NOGROUP.AS
>
> WITHOUT GENETIC GROUPS
> animal !P
> y
> nogroup.ped !ALPHA !MAKE
> nogroup.dat !MAXITER=20
> y ~ mu !r animal
>
> GROUP.AS
>
> WITH GENETIC GROUPS
> animal !P
> y
> group.ped !ALPHA !GROUPS 1 !MAKE
> group.dat !MAXITER=20
> y ~ mu !r animal
>
>
> --
> Asreml mailinglist archive: http://www.chiswick.anprod.csiro.au/lists/asreml
<><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><>
Arthur Gilmour PhD mailto:Arthur.Gilmour@agric.nsw.gov.au
Principal Research Scientist (Biometrics) fax: <61> 2 6391 3899
NSW Agriculture <61> 2 6391 3922
Orange Agricultural Institute telephone work: <61> 2 6391 3815
Forest Rd, ORANGE, 2800, AUSTRALIA home: <61> 2 6362 0046
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