tree.weight: Weights based on GSC Tree Method

In mdw: Maximum Diversity Weighting

Weights based on GSC Tree Method

Description

tree.weight Produce a set of weights for different end points based on a correlation matrix using the GSC tree method

Usage

tree.weight (cor.mat, method="GSC", clustering.method="average", plot=TRUE, 
    orientation=c("vertical","horizontal"), ...) 

Arguments

cor.mat	a matrix, correlation matrix
method	a string. GSC, implementation of Gerstein et al., is the only implemented currently
clustering.method	a string, how the bottom-up hierarchical clustering tree is built, is passed to hclust as the method parameter
plot	a Boolean, whether to plot the tree
orientation	vertical or horizontal
...	additional args

Value

A vector of weights that sum to 1.

Author(s)

Youyi Fong [e-mail]

References

Gerstein, M., Sonnhammer, E., and Chothia, C. (1994), Volume changes in protein evolution. J Mol Biol, 236, 1067-78.

Examples

cor.mat=diag(rep(1,3))
cor.mat[1,2]<-cor.mat[2,1]<-0.9
cor.mat[1,3]<-cor.mat[3,1]<-0.1
cor.mat[2,3]<-cor.mat[3,2]<-0.1
tree.weight(cor.mat)    

mdw documentation built on Sept. 11, 2024, 7:07 p.m.