Re: question to specify R structure.

Dear Jiqiu,

It is NOT true that PenComponent is always positive.
This is a restriction which is ofter sensible but not necessary.

In ASReml, just follow Pen with !GU to allow the pen component to be
negative,
implying a negative correlation (strong competion!).

adg ~ mu Sex !r Animal Pen !GU

><><><><><><><><><><><><><><><><><><><><><><><>

Jiqiu Cheng <Jiqiu.Cheng_at_BIW.KULEUVEN.BE>
Sent by: ASReml users discussion group <ASREML-L_at_AGRIC.NSW.GOV.AU>
09/12/2007 11:39 PM
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Re: question to specify R structure.

Quoting arthur.gilmour_at_DPI.NSW.GOV.AU:
Dear gilmour,
   Thank you for your quick reply first.
   As you suggested, "Fit Pen as a random factor, the error
correlation between pen-mates is given as the
PenComponent/(PenComponent+Residual)"
   However, the variance components of PenComponent and the residual
are always positive, which means that the error correlation between
pen-mates is always positive. But I think the correlation between
pen-mates could be negative too. So what do you think? Thanks.
   Best regards,

Jiqiu

> Dear Jiqiu Cheng
>
> You wrote
> A dataset include Animal and Pen effect. Pm1, Pdm2 and Pm3 are three
> penmates of the current animal. There are 2500 pens total, 4 animals
> each pen. I want to fit an R structure for which, animals within one
> pen are correlated and independent among different pens. The pen
> effects are independent.
>
> I tried to code the R structure as below:
>
> 1 2 0
> 2500 Pen ID
> CORU
>
> But it doesn't work. Could anyone give me any suggestions?
>
> Data set:
> Animal Sire Dam Sex Genation Pen Ai Pm1 Pm2 Pm3 adg
> 20751 10957 13673 2 3 1491 20751 23621 25420 27847 19.22
> 20752 10957 13673 2 3 1036 20752 23635 28874 29512 19.96
> 20753 10957 13673 2 3 2327 20753 22409 25602 26703 19.36
> 20754 10957 13673 2 3 2326 20754 21148 23208 30172 19.57
> 20755 10957 13673 2 3 2401 20755 22852 28577 29107 19.17
> 20756 10957 13673 1 3 782 20756 23266 23270 25910 -20.61
> 20757 10957 13673 1 3 983 20757 20815 21163 29738 -19.87
> 20758 10957 13673 1 3 1676 20758 21985 22899 23182 -19.31
> 20759 10957 13673 2 3 421 20759 27356 28702 29785 20.12
> 20760 10957 13673 2 3 308 20760 23035 29144 29441 18.84
>
>
> Assuming your data file has 10000 records so that the pen number say
1491
> appears 4 times in the file
> associated with the four animals 20751 23621 25420 27847
>
> Then you just need to fit Pen as a random factor
>
> Animals in Pens
> Animal !P Sire !P Dam !P
> Sex 2
> Genation
> Pen *
> Ai Pm1 Pm2 Pm3
> adg
> datafile.txt !skip 1 # read pedigree from data file
> datafile.txt !skip 1 # read data from data file
>
> adg ~ mu Sex !r Animal Pen
>
>
> This will give 3 variance components
> Pen
> Animal
> Residual
>
> The error correlation between pen-mates is given as
> the PenComponent/(PenComponent+Residual)
>
>
>
>
> May Jesus Christ be gracious to you,
>
> Arthur Gilmour, His servant .
>
> Mixed model regression mapping for QTL detection in experimental
crosses.
> Computational Statistics and Data Analysis 51:3749-3764 now available at
> http://dx.doi.org/10.1016/j.csda.2006.12.031
>
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>
> mailto:Arthur.Gilmour_at_dpi.nsw.gov.au, arthur_at_cargovale.com.au
> Principal Research Scientist (Biometrics)
> NSW Department of Primary Industries
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>
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Received on Fri Dec 10 2007 - 11:08:05 EST