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> From: Dr Ioan Ap Dewi <i.apdewi@bangor.ac.uk>
> To: "'asreml@ram.chiswick.anprod.csiro.au'"
<asreml@ram.chiswick.anprod.csiro.au>
> Subject: analysis of ww from ET data
> Date: Thu, 29 Apr 1999 16:41:21 +0100
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> I am analysing lamb weaning weight data from an experiment conducted
> over 2 years. There were sires from 6 origins (distinct areas) and
> ewes from 3 of these origins. Some origins had 1 sire/annum and
> others 2/annum. There were 12 ewes/origin/annum. Progeny were produced
> from all possible sire origin*dam origin combinations using ET to
> generate >1 progeny per sire-dam mating. The lambs were reared by
> recipient ewes that were unrelated to any of the sires or donor ewes.
> I have pedigree information for most of the sires and donors going
> back 1-3 generations. Some of the sires and donor ewes (within origins)
> were related. Some of the ancestors of sires and donor ewes were imported
> from identifiable farms.
>
> I have analysed the data in asreml with genetic groups. I have included
> groups representing the 6 origins and identifiable farms (i.e from
> which ancestors of donor sires and ewes were imported).
>
> Some lines form the pedigree file, data file and .as file are shown below.
>
> The researchers who conducted the field work were interested in whether
> there was an effect of origin and whether there was an interaction between
> origins.
>
> I would be grateful for comments about the method of analysis and
> interpretation of the output. My main queries are:-
>
> 1. Is the analysis appropriate ?
Given the information available, the analysis seems reasonable.
If you included so and do in the model, they should be
wholly singular since sires and dams are nested within origins.
However, there might be a so.do interaction so you
could test this [since each sire origin was mated to each dam origin].
> 2. How should I interpret the solutions for genetic groups.
> Can I determine from the solutions whether there is a significant
> effect of origins.
There is no group test of the significance of ORIGIN since it is
built into the relationship matrix. Because of the structure of the data,
I think you could drop the !GROUPS qualifier and then formally
include do so do.so in the model. It will not be exactly equivalent
because you have identified 27 groups but only have 6 origins.
Nevertheless you may be able to discern something from that analysis.
Alternatively, in the .sln file will be solutions for the group effects
with standard errors. IF one of these happens to be ZERO (singular),
then the others represent differences from the ZERO one.
Unfortunately, I cannot think of a way to make one SINGULAR
(= zero) so there will be no way of testing differences among them.
> 3. How can I determine if there is an interaction between origins ?
Try including do.so in the model.
>
> Thanks
>
I hope these alternative models do what I expect.
Arthur
> Ioan Ap Dewi
> School of Agricultural and Forest Sciences
> University of Wales
> Bangor, Gwynedd, LL57 2UW, UK
>
>
> #####
> example lines from pedigree file
> #####
> GR1 0 0
> .....
> .....
> GR27 0 0
> BA:0004 GR4 GR4
> CE:0005 GR5 GR5
> .....
> .....
> RH:0009 GR7 GR7
> CA:TC GR8 GR8
> LL:BCH81 GR11 GR11
> CP:CEIRO GR24 GR24
> CA:TN GR9 GR9
> LL:BD31 GR12 GR12
> .....
> .....
> CP:G888 CP:K999 CP:F852
> CA:W148 GR1 GR1
> LL:H52 GR27 GR27
> CP:G895 CP:K995 CP:K872
> CA:W195 GR1 GR1
> LL:H999 GR27 GR27
> .....
> .....
> 97015 CA:M006 CP:Y911
> 97016 BA:0004 LL:K050
> 97017 LL:L295 CA:K489
> 97018 CA:M006 LL:L118
> 97019 RH:0006 CA:K103
> 97021 CP:G959 LL:J074
> .....
> .....
> 98811 CE:0008 CA:L327
> 98812 CA:S461 LL:N331
> 98815 CE:0008 CP:Y924
> 98816 CA:S461 LL:N331
> 98817 CA:S461 LL:N331
> 98818 CE:0008 CP:G895
> 98819 CE:0008 CP:Y924
>
> ######
> example lines from data file
> ######
> 97001 CA:M006 CP:Y911 97 1 2 91335 6 2 42.5
> 97002 CE:0005 CA:J377 97 5 1 92066 5 1 34.5
> 97003 CP:G959 CA:W533 97 2 1 93240 4 1 38.5
> 97004 CE:0005 CP:W864 97 5 2 92312 5 1 44.5
> 97005 CA:M006 CP:Y911 97 1 2 92095 5 2 31.0
> 97006 CA:M006 CA:K517 97 1 1 92046 5 1 34.5
> 97007 CA:M006 LL:L118 97 1 3 91220 6 1 42.0
>
> ######
> .as file
> ######
> Analysis for ET Data
> animal !P
> sire !P
> gdam !P
> year 2 !I
> so 6 # sire origin
> do 3 # donor dam origin
> rdam 348 !I #identity of rearing dam
> rdage 4 !I #age of rearing dam
> sx 2 #sex of animal
> ww
> pedgr.dat !ALPHA !GROUPS 27 !NEW !MAKE
> wwall.dat
> ww ~ mu y sx rdage y.sx !r animal rdam
>
> --
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<><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><>
Arthur Gilmour PhD mailto:Arthur.Gilmour@agric.nsw.gov.au
Senior 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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