difconet (version 1.0-4)

difconet.plot.gene.correlations: PLOTS THE CORRELATIONS OF A SPECIFIC GENE

Description

Draw scatter plots of the correlations of a specific gene.

Usage

difconet.plot.gene.correlations(dObj, gene, 
  stages=1:length(dObj$stages.data), type=c("density","scatter")[1], 
  main=rownames(dObj$stages.data[[1]])[gene], 
  legends=TRUE, plot=TRUE, ... )

Arguments

dObj

The difconet object.

gene

Numeric or character. The gene index/rowname whose correlations will be drawn.

stages

Numeric or character. The stages to be included. If type="scatter" and more than two stages, a call to pairs is used instead of plot.

type

Character. The type of plot density or scatter.

main

Character. The main title passed to plot.

legends

Logical. Specifies whether the legends are drawn when type="density".

plot

Logical. Specifies whether the plots are actually drawn (to get the correlations).

...

Further parameters passed to plot/pairs.

Value

The correlations of the gene across stages (invisible).

Details

Run the whole process of estimation differences in correlations for a given dataset. The estimations are done for all metric values, all cutoff values across all comparisons.

References

Gonzalez-Valbuena and Trevino 2017 Metrics to Estimate Differential Co-Expression Networks Journal Pending volume 00--10

See Also

difconet.run.

Examples

xdata <- matrix(rnorm(1000), ncol=100)
xpredictor <- sample(c("A","B","C","D"),100,replace=TRUE)
dObj <- difconet.run(xdata, xpredictor, metric = 4, num_perms = 10,              
  comparisons = list(c("A","D"), c("A","B"), c("B","D")),
  perm_mode = "columns")

#Top highest metric in first comparison but showing correlations in only 3 stages
difconet.plot.gene.correlations(dObj, order(dObj$combstats[[1]][,"M4.dist"], 
  decreasing=TRUE)[1], type="s", stages=1:3)
#Bottom lowest metric in second comparison showing all stages
difconet.plot.gene.correlations(dObj, order(dObj$combstats[[2]][,"M4.dist"], 
  decreasing=TRUE)[1], type="d")
#Another specific gene (3), showing densities of correlations
difconet.plot.gene.correlations(dObj, 3, type="d")