Obtain box plots for the correlations of all celltypes, and the mean correlations at a specified cutoff p-value

correlation_boxplots(
  corrMats,
  numRealDatasets,
  pvals,
  alphaval = 0.25,
  numPerms = 5,
  numSubsets = 5,
  sexDEGs = FALSE,
  fontsize_yaxislabels = 12,
  fontsize_yaxisticks = 9,
  fontsize_title = 14,
  fontsize_legendlabels = 9,
  fontsize_legendtitle = 9,
  fontsize_facet_labels = 9,
  output_path = getwd()
)

Arguments

corrMats: (named) list of correlation matrices for each celltype with the final element being the mean correlation matrix, all at specified p-value
numRealDatasets: total number of real datasets (most likely the number of studies, but sometimes a study may be split e.g. into 2 brain regions, so in this case it would be the number of studies plus 1)
pvals: the cut-off p-value which was used to select DEGs
alphaval: (alpha) transparency of the non-mean boxplots
numPerms: number of random permutations of the dataset used to select significant DEGs from
numSubsets: number of pairs of random subsets of the dataset used to select significant DEGs from
sexDEGs: true if DEGs come from sex chromosomes, else false
fontsize_yaxislabels: font size for axis labels in plot
fontsize_yaxisticks: font size for axis tick labels in plot
fontsize_title: font size for plot title
fontsize_legendlabels: font size for legend labels in plot
fontsize_legendtitle: font size for legend title in plot
fontsize_facet_labels: font size for facet labels
output_path: base path in which outputs will be stored

Value

box plots for correlation matrices at a certain p-value cut-off, sorted by celltype and then type of correlation