如何创建具有系统发育校正的多元线性模型？
How to create a multivariate linear model with phylogenetic correction?
我正在尝试使用包 MCMCglmm 来 运行 一个经过系统发育校正的多元线性模型。这是我的数据的一个子集（67 个物种和 6 个簇共有 210 个条目）：
Names PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8 PC9 PC10 PC11 tips Clusters
Accipiter_gentilis1 -1.34E-01 1.98E-02 -1.72E-02 4.00E-02 -1.93E-03 2.45E-02 -1.28E-04 1.03E-02 9.09E-03 -5.33E-03 -1.30E-02 Accipiter_gentilis "Soaring"
Accipiter_gentilis2 -1.26E-01 1.22E-02 1.66E-02 9.22E-03 1.15E-02 1.68E-02 -1.50E-02 1.02E-02 7.93E-03 -8.47E-03 -1.02E-02 Accipiter_gentilis "Soaring"
Accipiter_nisus1 -1.81E-01 5.76E-02 -1.82E-02 6.15E-02 -9.25E-03 3.40E-02 -1.77E-02 5.45E-03 7.01E-03 -2.07E-02 -8.78E-03 Accipiter_nisus "Soaring"
Accipiter_nisus2 -2.00E-01 7.05E-02 -1.12E-02 5.94E-02 3.49E-03 3.10E-02 -1.58E-03 -1.55E-03 6.92E-03 -3.54E-02 -1.80E-02 Accipiter_nisus "Soaring"
Accipiter_nisus3 -8.14E-02 -3.39E-04 -8.88E-03 4.25E-02 -5.48E-04 -8.51E-03 5.07E-03 4.56E-03 1.97E-02 -1.46E-02 -1.43E-02 Accipiter_nisus "Soaring"
Accipiter_nisus4 -2.06E-01 7.05E-02 -2.17E-02 6.38E-02 -1.61E-02 2.80E-02 8.70E-03 -5.96E-03 6.15E-03 -5.29E-02 -2.05E-02 Accipiter_nisus "Soaring"
Actitis_hypoleucos1 2.27E-02 -2.74E-03 4.79E-02 -2.30E-02 -2.76E-02 -2.36E-02 1.70E-02 2.43E-03 3.82E-03 1.15E-02 -9.87E-03 Actitis_hypoleucos "Continuous flapping"
Actitis_hypoleucos2 6.67E-02 -1.05E-02 5.12E-02 -2.65E-02 -3.21E-02 -2.61E-02 3.21E-03 7.46E-03 7.29E-03 4.70E-03 -1.37E-02 Actitis_hypoleucos "Continuous flapping"
Aix_sponsa1 -3.70E-02 -1.41E-02 1.13E-02 3.16E-02 2.32E-02 -1.70E-02 2.32E-02 1.91E-03 2.91E-02 -7.71E-03 7.40E-03 Aix_sponsa "Continuous flapping"
Aix_sponsa2 1.03E-02 -4.08E-02 -6.62E-03 1.19E-02 2.83E-02 -1.49E-02 3.78E-02 6.98E-03 2.91E-02 -4.32E-03 2.54E-03 Aix_sponsa "Continuous flapping"
Aix_sponsa3 1.19E-02 -3.48E-02 -1.53E-02 3.76E-03 2.17E-02 1.47E-02 8.84E-03 2.39E-02 -9.20E-03 -1.78E-02 8.76E-04 Aix_sponsa "Continuous flapping"
Aix_sponsa4 -3.37E-02 -1.75E-02 -8.06E-03 3.64E-02 -5.50E-03 1.03E-02 2.37E-02 3.33E-03 -1.04E-03 -2.00E-02 5.89E-03 Aix_sponsa "Continuous flapping"
Aix_sponsa5 -2.30E-02 -9.59E-03 1.06E-02 3.01E-02 7.10E-03 -1.23E-02 2.08E-02 1.17E-02 1.59E-03 2.83E-03 8.75E-03 Aix_sponsa "Continuous flapping"
Aix_sponsa6 -1.70E-02 -2.98E-02 -1.96E-02 1.76E-02 1.23E-02 4.92E-03 5.45E-03 1.99E-02 -6.43E-03 -9.63E-04 1.99E-03 Aix_sponsa "Continuous flapping"
Aix_sponsa7 2.57E-02 -4.22E-02 -1.60E-02 1.75E-02 3.41E-03 5.80E-03 2.89E-02 6.10E-03 7.12E-03 2.75E-03 4.99E-03 Aix_sponsa "Continuous flapping"
Aix_sponsa8 4.09E-02 -4.46E-02 -4.49E-03 2.24E-02 2.37E-03 -5.90E-03 2.78E-02 -8.26E-04 1.17E-02 -5.71E-03 -1.77E-03 Aix_sponsa "Continuous flapping"
当我尝试 运行 单变量模型（下面的代码，phylo 指的是我的树）时它起作用了：
Ainv<-inverseA(phylo,nodes="TIPS",scale=F)$Ainv
p.var=var(data[,c("PC1")])
prior1<-list(R=list(V=(p.var),nu=0.002),G=list(G1=list(V=(p.var),nu=0.002)))
m7.phylo<-MCMCglmm(PC1~Clusters,
random=~tips,
family=rep("gaussian",1),
ginverse=list(tips=Ainv),
data=data,
prior=prior1)
但是，当我尝试制作多变量模型时，我收到错误消息：
Ainv<-inverseA(phylo,nodes="TIPS",scale=F)$Ainv
p.var=var(data[,c("PC1","PC2")])
prior1<-list(R=list(V=(diag(2)*p.var),nu=0.002),G=list(G1=list(V=(diag(2)*p.var),nu=0.002)))
m7.phylo<-MCMCglmm(cbind(PC1,PC2)~Clusters,
random=~tips,
family=rep("gaussian",2),
ginverse=list(tips=Ainv),
data=data,
prior=prior1)
Error in priorformat(if (NOpriorG) { :
V is the wrong dimension for some prior$G/prior$R elements
有人知道哪里出了问题吗？
谢谢，
卡罗莱纳州
所以这段代码似乎有效：
Ainv<-inverseA(phylo,nodes="TIPS",scale=F)$Ainv
p.var=var(data[,c(1:11)])
prior2<-list(R=list(V=p.var,nu=0.002),G=list(G1=list(V=p.var,nu=0.002)))
model2<-MCMCglmm(cbind(PC1,PC2,PC3,PC4,PC5,PC6,PC7,PC8,PC9,PC10,PC11)~Clusters,
random = ~us(trait):tips,
rcov = ~idh(trait):units,
family=rep("gaussian",11),
ginverse=list(tips=Ainv),
data=data,
prior=prior2)
它似乎在做我想让它做的事，但我真的没有信心说我知道的足够多！如有任何意见，我们将不胜感激！
编辑：与其他人讨论过这个问题，这似乎与他们提供的解决方案一致，所以我认为它是正确的。
我正在尝试使用包 MCMCglmm 来 运行 一个经过系统发育校正的多元线性模型。这是我的数据的一个子集（67 个物种和 6 个簇共有 210 个条目）：
Names PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8 PC9 PC10 PC11 tips Clusters
Accipiter_gentilis1 -1.34E-01 1.98E-02 -1.72E-02 4.00E-02 -1.93E-03 2.45E-02 -1.28E-04 1.03E-02 9.09E-03 -5.33E-03 -1.30E-02 Accipiter_gentilis "Soaring"
Accipiter_gentilis2 -1.26E-01 1.22E-02 1.66E-02 9.22E-03 1.15E-02 1.68E-02 -1.50E-02 1.02E-02 7.93E-03 -8.47E-03 -1.02E-02 Accipiter_gentilis "Soaring"
Accipiter_nisus1 -1.81E-01 5.76E-02 -1.82E-02 6.15E-02 -9.25E-03 3.40E-02 -1.77E-02 5.45E-03 7.01E-03 -2.07E-02 -8.78E-03 Accipiter_nisus "Soaring"
Accipiter_nisus2 -2.00E-01 7.05E-02 -1.12E-02 5.94E-02 3.49E-03 3.10E-02 -1.58E-03 -1.55E-03 6.92E-03 -3.54E-02 -1.80E-02 Accipiter_nisus "Soaring"
Accipiter_nisus3 -8.14E-02 -3.39E-04 -8.88E-03 4.25E-02 -5.48E-04 -8.51E-03 5.07E-03 4.56E-03 1.97E-02 -1.46E-02 -1.43E-02 Accipiter_nisus "Soaring"
Accipiter_nisus4 -2.06E-01 7.05E-02 -2.17E-02 6.38E-02 -1.61E-02 2.80E-02 8.70E-03 -5.96E-03 6.15E-03 -5.29E-02 -2.05E-02 Accipiter_nisus "Soaring"
Actitis_hypoleucos1 2.27E-02 -2.74E-03 4.79E-02 -2.30E-02 -2.76E-02 -2.36E-02 1.70E-02 2.43E-03 3.82E-03 1.15E-02 -9.87E-03 Actitis_hypoleucos "Continuous flapping"
Actitis_hypoleucos2 6.67E-02 -1.05E-02 5.12E-02 -2.65E-02 -3.21E-02 -2.61E-02 3.21E-03 7.46E-03 7.29E-03 4.70E-03 -1.37E-02 Actitis_hypoleucos "Continuous flapping"
Aix_sponsa1 -3.70E-02 -1.41E-02 1.13E-02 3.16E-02 2.32E-02 -1.70E-02 2.32E-02 1.91E-03 2.91E-02 -7.71E-03 7.40E-03 Aix_sponsa "Continuous flapping"
Aix_sponsa2 1.03E-02 -4.08E-02 -6.62E-03 1.19E-02 2.83E-02 -1.49E-02 3.78E-02 6.98E-03 2.91E-02 -4.32E-03 2.54E-03 Aix_sponsa "Continuous flapping"
Aix_sponsa3 1.19E-02 -3.48E-02 -1.53E-02 3.76E-03 2.17E-02 1.47E-02 8.84E-03 2.39E-02 -9.20E-03 -1.78E-02 8.76E-04 Aix_sponsa "Continuous flapping"
Aix_sponsa4 -3.37E-02 -1.75E-02 -8.06E-03 3.64E-02 -5.50E-03 1.03E-02 2.37E-02 3.33E-03 -1.04E-03 -2.00E-02 5.89E-03 Aix_sponsa "Continuous flapping"
Aix_sponsa5 -2.30E-02 -9.59E-03 1.06E-02 3.01E-02 7.10E-03 -1.23E-02 2.08E-02 1.17E-02 1.59E-03 2.83E-03 8.75E-03 Aix_sponsa "Continuous flapping"
Aix_sponsa6 -1.70E-02 -2.98E-02 -1.96E-02 1.76E-02 1.23E-02 4.92E-03 5.45E-03 1.99E-02 -6.43E-03 -9.63E-04 1.99E-03 Aix_sponsa "Continuous flapping"
Aix_sponsa7 2.57E-02 -4.22E-02 -1.60E-02 1.75E-02 3.41E-03 5.80E-03 2.89E-02 6.10E-03 7.12E-03 2.75E-03 4.99E-03 Aix_sponsa "Continuous flapping"
Aix_sponsa8 4.09E-02 -4.46E-02 -4.49E-03 2.24E-02 2.37E-03 -5.90E-03 2.78E-02 -8.26E-04 1.17E-02 -5.71E-03 -1.77E-03 Aix_sponsa "Continuous flapping"
当我尝试 运行 单变量模型（下面的代码，phylo 指的是我的树）时它起作用了：
Ainv<-inverseA(phylo,nodes="TIPS",scale=F)$Ainv
p.var=var(data[,c("PC1")])
prior1<-list(R=list(V=(p.var),nu=0.002),G=list(G1=list(V=(p.var),nu=0.002)))
m7.phylo<-MCMCglmm(PC1~Clusters,
random=~tips,
family=rep("gaussian",1),
ginverse=list(tips=Ainv),
data=data,
prior=prior1)
但是，当我尝试制作多变量模型时，我收到错误消息：
Ainv<-inverseA(phylo,nodes="TIPS",scale=F)$Ainv
p.var=var(data[,c("PC1","PC2")])
prior1<-list(R=list(V=(diag(2)*p.var),nu=0.002),G=list(G1=list(V=(diag(2)*p.var),nu=0.002)))
m7.phylo<-MCMCglmm(cbind(PC1,PC2)~Clusters,
random=~tips,
family=rep("gaussian",2),
ginverse=list(tips=Ainv),
data=data,
prior=prior1)
Error in priorformat(if (NOpriorG) { :
V is the wrong dimension for some prior$G/prior$R elements
有人知道哪里出了问题吗？
谢谢，
卡罗莱纳州
所以这段代码似乎有效：
Ainv<-inverseA(phylo,nodes="TIPS",scale=F)$Ainv
p.var=var(data[,c(1:11)])
prior2<-list(R=list(V=p.var,nu=0.002),G=list(G1=list(V=p.var,nu=0.002)))
model2<-MCMCglmm(cbind(PC1,PC2,PC3,PC4,PC5,PC6,PC7,PC8,PC9,PC10,PC11)~Clusters,
random = ~us(trait):tips,
rcov = ~idh(trait):units,
family=rep("gaussian",11),
ginverse=list(tips=Ainv),
data=data,
prior=prior2)
它似乎在做我想让它做的事，但我真的没有信心说我知道的足够多！如有任何意见，我们将不胜感激！
编辑：与其他人讨论过这个问题，这似乎与他们提供的解决方案一致，所以我认为它是正确的。