R/validate_input_parameters_correlation.r
validate_input_parameters_correlation.RdTests input parameters for functions
validate_input_parameters_correlation(
dataset_name = "placeholder",
allstudies = "placeholder",
celltypes = "placeholder",
pvalue = "placeholder",
data_names = "placeholder",
corrMats = "placeholder",
numRealDatasets = "placeholder",
alphaval = "placeholder",
numPerms = "placeholder",
numSubsets = "placeholder",
sexDEGs = "placeholder",
fontsize_yaxislabels = "placeholder",
fontsize_yaxisticks = "placeholder",
fontsize_title = "placeholder",
fontsize_legendlabels = "placeholder",
fontsize_legendtitle = "placeholder",
fontsize_facet_labels = "placeholder",
output_path = "placeholder"
)name of the dataset used to select significant DEGs from (specified as a string, name as in allStudies)
a list containing all the datasets (most likely as SCE objects)
a list containing the celltypes to compute mean correlation across
the cut-off p-value which will be used to select DEGs
names of the datasets as they appear in the correlation plot
(named) list of correlation matrices for each celltype with the final element being the mean correlation matrix, all at specified p-value
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)
(alpha) transparency of the non-mean boxplots
number of random permutations of the dataset used to select significant DEGs from
number of pairs of random subsets of the dataset used to select significant DEGs from
true if DEGs come from sex chromosomes, else false
font size for axis labels in plot
font size for axis tick labels in plot
font size for plot title
font size for legend labels in plot
font size for legend title in plot
font size for facet labels
base path in which outputs will be stored Checks all correlation analysis parameters are specified correctly