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<DIV><FONT size=2 face=Arial><FONT color=#0000ff size=3>Eu rodei o script e me
deu erro aqui, por que?</FONT> </FONT></DIV>
<DIV><FONT size=2 face=Arial></FONT> </DIV>
<DIV><FONT size=2 face=Arial>fm2 <- pedigreemm(Prod ~ (1|id) + Local1/Corte1
+ (1|Local1/Bloco1), data = dat2, pedigree = list(id = pedCana))<BR></FONT><FONT
size=2 face=Arial>Error in solve(t(as(ped, "sparseMatrix")), as(factor(labs,
levels = <A href="mailto:ped@label">ped@label</A>), : <BR>
Dimensions of system to be solved are inconsistent<BR></FONT><BR></DIV>
<BLOCKQUOTE
style="BORDER-LEFT: #000000 2px solid; PADDING-LEFT: 5px; PADDING-RIGHT: 0px; MARGIN-LEFT: 5px; MARGIN-RIGHT: 0px">
<DIV dir=ltr>
<DIV>Bom dia!!</DIV>
<DIV> </DIV>
<DIV>Pessoal, ajustei um modelo utilizando a função pedigreemm
(incorporando a informação do pedigree) e lmer (do pacote, lme4, sem o
pedigree). Notei que os BLUps obtidos (via ranef) com a pedigreemm são
maiores do que os obtidos com a lmer.</DIV>
<DIV> </DIV>
<DIV>A dúvida é que acredito que quando usamos a informação do
pedigree, predizemos o <STRONG>Valor Genético Aditivo</STRONG>
(<EM>Breeding Values</EM>). E quando não utilizamos a informação do pedigree,
predizemos o <STRONG>Valor Genético Total</STRONG> (<EM>incluindo os efeitos
aditivos, dominância e epistático</EM>), por isso esperava maiores valores dos
BLUPs.</DIV>
<DIV> </DIV>
<DIV> </DIV>
<DIV>Será que alguém pode me esclarecer??</DIV>
<DIV> </DIV>
<DIV>Segue a rotina e dados em anexo:</DIV>
<DIV> </DIV>
<DIV>
<P style="LINE-HEIGHT: normal; MARGIN: 0cm 0cm 0pt" class=MsoNormal><SPAN
style="FONT-FAMILY: 'Arial','sans-serif'; FONT-SIZE: 10pt">#-----------------------------------------------------------------------------<BR>#
EXEMPLO:<BR># Variável analisada: Prod<BR># Número de indivíduos no pedigree:
9<BR># Número de indivíduos com informação fenotipica: 5<BR># Número de bloco:
3<BR># Número de corte: 2<BR># Número de local:
3<BR>#------------------------------------------------------------------------------</SPAN></P>
<P style="LINE-HEIGHT: normal; MARGIN: 0cm 0cm 0pt" class=MsoNormal><SPAN
style="FONT-FAMILY: 'Arial','sans-serif'; FONT-SIZE: 10pt">rm(list =
ls())</SPAN></P>
<P style="LINE-HEIGHT: normal; MARGIN: 0cm 0cm 0pt" class=MsoNormal><SPAN
style="FONT-FAMILY: 'Arial','sans-serif'; FONT-SIZE: 10pt"></SPAN> </P><SPAN
style="FONT-FAMILY: 'Arial','sans-serif'; FONT-SIZE: 10pt">
<P style="LINE-HEIGHT: normal; MARGIN: 0cm 0cm 0pt" class=MsoNormal><SPAN
style="FONT-FAMILY: 'Arial','sans-serif'; FONT-SIZE: 10pt"></SPAN> </P>
<P style="LINE-HEIGHT: normal; MARGIN: 0cm 0cm 0pt" class=MsoNormal><SPAN
style="FONT-FAMILY: 'Arial','sans-serif'; FONT-SIZE: 10pt"><STRONG>1 - Com
o pedigree</STRONG></SPAN></P></SPAN><SPAN
style="FONT-FAMILY: 'Arial','sans-serif'; FONT-SIZE: 10pt">
<P style="LINE-HEIGHT: normal; MARGIN: 0cm 0cm 0pt"
class=MsoNormal><BR><STRONG># reading pedigree file</STRONG></P>
<P style="LINE-HEIGHT: normal; MARGIN: 0cm 0cm 0pt"
class=MsoNormal><BR>dadped<-read.table("genealogia2.csv", head=T, sep=";",
dec=",")</P></SPAN>
<P style="LINE-HEIGHT: normal; MARGIN: 0cm 0cm 0pt" class=MsoNormal></P>
<P style="LINE-HEIGHT: normal; MARGIN: 0cm 0cm 0pt" class=MsoNormal><SPAN
style="FONT-FAMILY: 'Arial','sans-serif'; FONT-SIZE: 10pt">head(dadped)<BR>require(lme4)<BR>require(pedigreemm)</SPAN></P>
<P style="LINE-HEIGHT: normal; MARGIN: 0cm 0cm 0pt" class=MsoNormal><SPAN
style="FONT-FAMILY: 'Arial','sans-serif'; FONT-SIZE: 10pt"></SPAN> </P>
<P style="LINE-HEIGHT: normal; MARGIN: 0cm 0cm 0pt" class=MsoNormal><SPAN
style="FONT-FAMILY: 'Arial','sans-serif'; FONT-SIZE: 10pt"><STRONG>#
Constructing pedigree</STRONG></SPAN></P><SPAN
style="FONT-FAMILY: 'Arial','sans-serif'; FONT-SIZE: 10pt">
<P style="LINE-HEIGHT: normal; MARGIN: 0cm 0cm 0pt"
class=MsoNormal><BR>pedCana <- pedigree(sire =
as.integer(dadped$Dad),<BR>
dam =
as.integer(dadped$Mon),<BR>
label= as.character(1:9))<BR>fac <- relfactor(pedCana)<BR>MpedCana <-
crossprod(fac)</P>
<P style="LINE-HEIGHT: normal; MARGIN: 0cm 0cm 0pt"
class=MsoNormal> </P></SPAN>
<P style="LINE-HEIGHT: normal; MARGIN: 0cm 0cm 0pt" class=MsoNormal></P>
<P style="LINE-HEIGHT: normal; MARGIN: 0cm 0cm 0pt" class=MsoNormal><FONT
face="Times New Roman"><STRONG># reading phenotype
file</STRONG></FONT></P><FONT face="Times New Roman">
<P style="LINE-HEIGHT: normal; MARGIN: 0cm 0cm 0pt"
class=MsoNormal><BR>dat2<-read.table("dados_sem_ascestrais.csv", head=T,
sep=";", dec=",", na.strings="NA")<BR>head(dat2)<BR>attach(dat2)</P>
<P style="LINE-HEIGHT: normal; MARGIN: 0cm 0cm 0pt" class=MsoNormal><BR>Bloco1
<- factor(bloco)<BR>Corte1 <- factor(corte)<BR>Local1 <-
factor(local)</P>
<P style="LINE-HEIGHT: normal; MARGIN: 0cm 0cm 0pt"
class=MsoNormal> </P></FONT>
<P style="LINE-HEIGHT: normal; MARGIN: 0cm 0cm 0pt" class=MsoNormal></P>
<P style="LINE-HEIGHT: normal; MARGIN: 0cm 0cm 0pt" class=MsoNormal><FONT
face="Times New Roman"><STRONG><FONT size=+0># <FONT
face=arial,helvetica,sans-serif>fitting model with
pedigree</FONT></FONT></STRONG></FONT></P>
<P style="LINE-HEIGHT: normal; MARGIN: 0cm 0cm 0pt" class=MsoNormal><FONT
face=arial,helvetica,sans-serif></FONT> </P>
<P style="LINE-HEIGHT: normal; MARGIN: 0cm 0cm 0pt" class=MsoNormal><FONT
face=arial,helvetica,sans-serif>fm2 <- pedigreemm(Prod ~ (1|id) +
Local1/Corte1 + (1|Local1/Bloco1), data = dat2, pedigree = list(id =
pedCana))</FONT></P>
<P style="LINE-HEIGHT: normal; MARGIN: 0cm 0cm 0pt" class=MsoNormal><FONT
face="Times New Roman"><BR><FONT size=+0><FONT
face=arial,helvetica,sans-serif>BLUP.a <- ranef(fm2)$id;
BLUP.a <STRONG>
# BLUPs dos efeitos genéticos aditivo</STRONG></FONT>
</FONT></FONT></P><FONT face="Times New Roman">
<P style="LINE-HEIGHT: normal; MARGIN: 0cm 0cm 0pt" class=MsoNormal> </P>
<P style="LINE-HEIGHT: normal; MARGIN: 0cm 0cm 0pt"
class=MsoNormal> </P><SPAN
style="FONT-FAMILY: 'Arial','sans-serif'; FONT-SIZE: 10pt">
<P style="LINE-HEIGHT: normal; MARGIN: 0cm 0cm 0pt" class=MsoNormal> </P>
<P style="LINE-HEIGHT: normal; MARGIN: 0cm 0cm 0pt" class=MsoNormal><SPAN
style="FONT-FAMILY: 'Arial','sans-serif'; FONT-SIZE: 10pt"><STRONG>2 - Sem
o pedigree</STRONG></SPAN></P></SPAN>
<P style="LINE-HEIGHT: normal; MARGIN: 0cm 0cm 0pt"
class=MsoNormal> </P></FONT>
<P style="LINE-HEIGHT: normal; MARGIN: 0cm 0cm 0pt" class=MsoNormal><SPAN
style="FONT-FAMILY: 'Arial','sans-serif'; FONT-SIZE: 10pt"><STRONG> #
fitting model without pedigree</STRONG></SPAN></P>
<P style="LINE-HEIGHT: normal; MARGIN: 0cm 0cm 0pt" class=MsoNormal><SPAN
style="FONT-FAMILY: 'Arial','sans-serif'; FONT-SIZE: 10pt"></SPAN> </P>
<P style="LINE-HEIGHT: normal; MARGIN: 0cm 0cm 0pt" class=MsoNormal><SPAN
style="FONT-FAMILY: 'Arial','sans-serif'; FONT-SIZE: 10pt">fm3 <-lmer(Prod
~ (1|id) + Local1/Corte1 + (1|Local1/Bloco1), data = dat2)</SPAN></P><SPAN
style="FONT-FAMILY: 'Arial','sans-serif'; FONT-SIZE: 10pt">
<P style="LINE-HEIGHT: normal; MARGIN: 0cm 0cm 0pt" class=MsoNormal><BR>BLUP.g
<- ranef(fm3)$id;
BLUP.g <STRONG># BLUPs
dos efeitos genéticos (aditivo + dominância +
epistáticos)<BR></STRONG></P>
<P style="LINE-HEIGHT: normal; MARGIN: 0cm 0cm 0pt"
class=MsoNormal>data.frame(BLUP.g,
BLUP.a)
<STRONG># BLUPs dos efeitos genéticos e genéticos aditivo</STRONG></P></SPAN>
<P style="LINE-HEIGHT: normal; MARGIN: 0cm 0cm 0pt" class=MsoNormal> </P>
<P style="LINE-HEIGHT: normal; MARGIN: 0cm 0cm 0pt"
class=MsoNormal><STRONG>Resultados:</STRONG></P>
<P style="LINE-HEIGHT: normal; MARGIN: 0cm 0cm 0pt"
class=MsoNormal><STRONG></STRONG> </P>
<P style="LINE-HEIGHT: normal; MARGIN: 0cm 0cm 0pt" class=MsoNormal><FONT
face="Times New Roman"><STRONG>> fm2</STRONG><BR>Linear mixed model fit by
REML <BR>Formula: Prod ~ (1 | id) + Local1/Corte1 + (1 | Local1/Bloco1)
<BR> Data: dat2 <BR> AIC BIC logLik
deviance REMLdev<BR> 764.3 789.3 -372.1
777.8 744.3<BR>Random
effects:<BR> Groups
Name Variance
Std.Dev. <BR> Bloco1:Local1 (Intercept) 1.0992e-13
3.3155e-07<BR> id
(Intercept) 4.8287e+00
2.1974e+00<BR> Local1
(Intercept) 3.0252e+01
5.5002e+00<BR> Residual
3.3712e+02 1.8361e+01<BR>Number of obs: 90, groups: Bloco1:Local1, 9; id, 5;
Local1, 3</FONT></P>
<P style="LINE-HEIGHT: normal; MARGIN: 0cm 0cm 0pt" class=MsoNormal><FONT
face="Times New Roman"><BR></FONT> </P>
<P style="LINE-HEIGHT: normal; MARGIN: 0cm 0cm 0pt" class=MsoNormal><FONT
face="Times New Roman"><STRONG>> fm3</STRONG><BR>Linear mixed model fit by
REML <BR>Formula: Prod ~ (1 | id) + Local1/Corte1 + (1 | Local1/Bloco1)
<BR> Data: dat2 <BR> AIC BIC logLik
deviance REMLdev<BR> 764.4 789.4 -372.2
777.8 744.4<BR>Random
effects:<BR> Groups
Name Variance
Std.Dev. <BR> Bloco1:Local1 (Intercept) 1.1257e-17
3.3551e-09<BR> id
(Intercept) 1.3792e+00
1.1744e+00<BR> Local1
(Intercept) 2.9551e+01
5.4361e+00<BR> Residual
3.3926e+02 1.8419e+01<BR>Number of obs: 90, groups: Bloco1:Local1, 9; id, 5;
Local1, 3</FONT></P>
<P style="LINE-HEIGHT: normal; MARGIN: 0cm 0cm 0pt" class=MsoNormal><FONT
face="Times New Roman"></FONT> </P>
<P style="LINE-HEIGHT: normal; MARGIN: 0cm 0cm 0pt" class=MsoNormal><FONT
face="Times New Roman"><STRONG>> data.frame(BLUP.g,
BLUP.a)</STRONG><BR> X.Intercept. X.Intercept..1<BR>5 <FONT
style="BACKGROUND-COLOR: rgb(255,0,0)">0.04624036
0.4146977<BR></FONT>6 -0.51780417
-1.1289438<BR>7 <A href="tel:0.30066464" target=_blank
value="+5530066464"><FONT
color=#0066cc>0.30066464</FONT></A>
1.2858838<BR>8 0.06359092
0.1372509<BR>9 0.10730825
0.2615716</FONT><BR>-- <BR><SPAN
style="COLOR: rgb(102,102,102)">=================================================</SPAN><BR
style="COLOR: rgb(102,102,102)"><SPAN style="COLOR: rgb(102,102,102)">Edjane
Gonçalves de Freitas</SPAN><BR style="COLOR: rgb(102,102,102)"><SPAN
style="COLOR: rgb(102,102,102)">Engenheira Agrônoma - UFAL</SPAN><BR
style="COLOR: rgb(102,102,102)"><SPAN
style="COLOR: rgb(102,102,102)">Doutoranda - Lab. Genética e
Estatística</SPAN><BR style="COLOR: rgb(102,102,102)"><FONT
style="COLOR: rgb(102,102,102)" color=#888888>Departamento de Genética e
Melhoramento de Plantas - ESALQ/USP<BR>Cel: (19) 8102-7790</FONT><BR
style="COLOR: rgb(102,102,102)"></P></DIV></DIV></BLOCKQUOTE></BODY></HTML>