Open MKLau opened 10 years ago
This can be done by getting the co-occurrence matrix, which is a tree by unique, non-recursive species pairs matrix, and testing for the genetic effect using PerMANOVA.
coMat = function(x){ y=list() k=0 for (i in 1:ncol(x)){ for (j in i:ncol(x)){ k=k+1 if (i!=j){ y[[k]]=sign(x[,i]+x[,j]) names(y)[k]=paste(colnames(x)[i],colnames(x)[j],sep='_') } } } y=do.call(cbind,y) return(y) }
adonis(formula = com ~ g)
Source Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
g 9 2.6272 0.29191 1.3968 0.2953 0.009 **
Residuals 30 6.2696 0.20899 0.7047
Total 39 8.8968 1.0000
adonis(formula = test ~ g)
Source Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
g 9 1.8614 0.20682 1.2643 0.27499 0.028 *
Residuals 30 4.9075 0.16359 0.72501
Total 39 6.7690 1.00000
0) needs replication at the tree scale 1) for each tree, build a vector of the number of n-wise co-occurrences 2) build a tree by co-occurrence pairs/groups matrix 3) test for genotypic effects using Bray-Curtis PerMANOVA