[R-sig-ME] animal model: calculating heritability and evolvability from sire effects

[Pierre B. de Villemereuil]

Mikhail,

I've been thinking at your issue, and here's what I thought : you only 
have average phenotype of the offspring of a sire, right ? If I 
understand correctly, this means you already have your sire effect ! 
What I mean by this is that, by taking the average, you get rid of the 
residual variations. So if you withdraw the mean phenotype from each 
value (which already is the average value by sires), the rest should be 
the sire effect.

This way, the variance of your phenotypic values are directly sire 
variance. However, you don't have access to the real phenotypic variance 
(Vp), which is necessary to estimate heritability... Maybe you could 
estimate the residual variance (or the within-family variance) from a 
family subset ?

Excuse-me if I didn't understand correctly your experimental design...

Cheers,
Pierre.

Le 30/12/2011 08:01, mikhail matz a écrit :
> Hi Pierre -
>
> My full-sib families of larvae are thousands strong. I typically put 50 or more individuals into a single measurement, so I would consider them reasonably close to family-wise averages. Also, I can cross as many sires with as many dams as I want (actually, as many as I can handle, bucket-wise). In my current experiment, two dams were crossed with the same ten sires each, so I am looking at 20 full-sib families. This should give me reasonably good estimate of the size of sire effects, don't you think?
>
> M
>
> On Dec 29, 2011, at 4:31 AM, Pierre B. de Villemereuil wrote:
>
>> Hi !
>>
>> I'm wondering if you noticed my e-mail on the R list, so I'm transferring it to you, just in case !
>>
>> I'm still puzzled by your design : could you explain it further to me ? You say you have a full-sibs design and estimating sire effect : is that to say you have the offspring of one male (sire) and one female (dam) for each sire ? Or only one dam, and several sire ?
>>
>> And also, if I understand correctly, you don't have individual measurement for the offspring, but only the average sibling phenotype, is that right ? And you don't have parents phenotype ?
>>
>> Cheers,
>> Pierre.
>>
>> -------- Message original --------
>> Sujet:	Re: [R-sig-ME] animal model: calculating heritability and evolvability from sire effects
>> Date :	Wed, 21 Dec 2011 21:56:21 +0100
>> De :	Pierre B. de Villemereuil<bonamy at horus.ens.fr>
>> Répondre à :	bonamy at horus.ens.fr
>> Pour :	r-sig-mixed-models at r-project.org
>>
>> Hi !
>>
>> Concerning the 4 coefficient : you say the additive variance is
>> estimated within the full-sibs of the same sire. Is that to say
>> offspring of the same sire descent as well from the same dam ? In that
>> case (same father and same mother), then the relationship coefficient is
>> of 1/2 (2 * coefficient of coancestry of 1/4). So, I think (but I can be
>> wrong) the coefficient should be 2.
>>
>> If each individual descent from a different mother, then kinship is 1/4.
>> So the coefficient of 4 is correct.
>>
>> When estimating the heritability of a binomial trait, you have to keep
>> the residual variance in the total variance. Just add the 'link
>> variance' (say Vlink) such as :
>> h² = Va / (Va + Vr + Vlink)    (Vlink is pi²/3 for logit link and 1 for
>> probit link)
>>
>> Cheers,
>> Pierre.
>>
>> Le 21/12/2011 12:18, Szymek Drobniak a écrit :
>>> Hi,
>>>
>>> both your code and the way you calculate VA using sire variance seems
>>> fine. In lmer residual variance is fixed as it assumes fixed
>>> relationship between variance and mean in binomial data so I'm not
>>> sure if simply putting this variance in your formula solves the
>>> problem. In MCMCglmm residual variance quantifies overdispersion so as
>>> far as I know here it's just a matter of substituting gaussian to
>>> multinomial2.
>>>
>>> Cheers,
>>> sz.
>>>
>>> --
>>> Szymon Drobniak || Population Ecology Group
>>> Institute of Environmental Sciences, Jagiellonian University
>>> ul. Gronostajowa 7, 30-387 Kraków, POLAND
>>> tel.: +48 12 664 51 79 fax: +48 12 664 69 12
>>>
>>>
>> www.eko.uj.edu.pl/drobniak
>>
>>> _______________________________________________
>>>
>> R-sig-mixed-models at r-project.org
>>   mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>>
>>
>> _______________________________________________
>>
>> R-sig-mixed-models at r-project.org
>>   mailing list
>>
>> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models