CVPlot: Make correlation vector plot

In compmedlab/MCbiclust: Massive correlating biclusters for gene expression data and associated methods

Description

A function to visualise the differences between different found biclusters. Output is a matrix of plots. Each correlation vector is plotted against each other across the entire measured gene set in the lower diagonal plots, and a chosen gene set (e.g. mitochondrial) in the upper diagonal plots. The diagnal plots themselves show the density plots of the entire measured and chosen gene set. There are addition options to set the transparancy of the data points and names of the correlation vectors.

Usage

CVPlot(cv.df, geneset.loc, geneset.name, alpha1 = 0.005, alpha2 = 0.1,
  cnames = NULL)

Arguments

cv.df	A dataframe containing the correlation vectors of one or more patterns.
geneset.loc	A gene set of interest (e.g. mitochondrial) to be plotted separately from rest of genes.
geneset.name	Name of geneset (e.g. mitochondrial genes)
alpha1	Transparency level of non-gene set genes
alpha2	Transparency level of gene set genes
cnames	Character vector containing names for the correlation vector

Value

A plot of the correlation vectors

Examples

data(CCLE_small)
data(Mitochondrial_genes)

mito.loc <- which(row.names(CCLE_small) %in% Mitochondrial_genes)
CCLE.mito <- CCLE_small[mito.loc,]

CCLE.seed <- list()
CCLE.cor.vec <- list()

for(i in 1:3){
    set.seed(i)
    CCLE.seed[[i]] <- FindSeed(gem = CCLE.mito,
                               seed.size = 10,
                               iterations = 100,
                               messages = 100)}

for(i in 1:3){
    CCLE.cor.vec[[i]] <-  CVEval(gem.part = CCLE.mito,
                                 gem.all = CCLE_small,
                                 seed = CCLE.seed[[i]],
                                splits = 10)}



CCLE.cor.df <- (as.data.frame(CCLE.cor.vec))

CVPlot(cv.df = CCLE.cor.df, geneset.loc = mito.loc,
       geneset.name = "Mitochondrial",alpha1 = 0.5)

compmedlab/MCbiclust documentation built on March 9, 2020, 12:14 a.m.