dplot {Prize}R Documentation

dplot

Description

Computing and plotting the distance between individuals and group judgement. Distances are computed using classical multidimensional scaling (MDS) approach.

Usage

dplot(srcfile, fontsize = 15, xcex = 10, ycex = 10, lcex = 5,
  hjust = 0.5, vjust = 1, xlab = "Coordinate 1", ylab = "Coordinate 2",
  main = NULL)

Arguments

srcfile

a numeric matrix of individual and group priorities.

fontsize

the font size of the plot title, and x and y axis labels. The default value is 15.

xcex,ycex

the font size of the x and y axis, respectively. The default values is 10.

lcex

the font size of point labels in dplot

hjust,vjust

the horizontal and vertical justification of point labels, respectively.

xlab,ylab

the label of the x and y axis, respectively.

main

the plot title

Value

An object created by 'ggplot'.

Author(s)

Daryanaz Dargahi

References

J.C. Gower. Some distance properties of latent root and vector methods used in multivariate analysis. Biometrika, 53(3/4):pp. 325-338, 1966.

Examples

mat <- matrix(nrow = 5, ncol = 4, data = NA)
rownames(mat) <- c('Ind1','Ind2','Ind3', 'Ind4' ,'Group judgement')
colnames(mat) <- c('Tumor_expression','Normal_expression','Frequency','Epitopes')
mat[1,] <- c(0.4915181, 0.3058879, 0.12487821, 0.07771583)
mat[2,] <- c(0.3060687, 0.4949012, 0.12868606, 0.07034399)
mat[3,] <- c(0.4627138, 0.3271881, 0.13574662, 0.07435149)
mat[4,] <- c(0.6208484, 0.2414021, 0.07368481, 0.06406465)
mat[5,] <- c(0.4697298, 0.3406738, 0.11600194, 0.07359445)

dplot(mat, xlab = 'Coordinate 1', ylab = 'Coordinate 2', main = 'Distance plot')

[Package Prize version 1.17.0 Index]