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#' Calculate p-value from bootstrapped sample
#'
#' @description The distribution of microdissected tissues supporting each
#' larger brain region is not equal across all regions. We therefore provide
#' an option to bootstrap gene set enrichment. This function calculates
#' the signficance of that enrichment.
#'
#' \code{PValue.onetail} Calculates the p-value from a bootstrapped sample
#'
#' @param regions character regions to search
#' @param tissueExp1 numeric vector presence of genes in query
#' @param random.matrix numeric presence of genes at random
#' @return p-value of the significance of tissueExp1 given the random.matrix
#' @importFrom stats na.exclude
#'
#' @examples
#' ##Internal to brainImageR, called within testEnrich
#' #brainImageR:::loadworkspace()
#' ##First put together a gene list, or load in the default vth dataset
#' data(vth)
#' ##Calculate the spatial enrichment.
#' #composite <- SpatialEnrichment(vth, reps = 20, refset = "developing")
#' #tissueExp1 <- composite@tissueExp1
#' #random.matrix <- composite@random.matrix
#' #boot <- PValue.onetail(regions = names(tissueExp1),
#' #tissueExp1,
#' #random.matrix)
#'
#'@export
PValue.onetail <- function(regions,tissueExp1,random.matrix){
a <- na.exclude(random.matrix[regions,])
b <- tissueExp1[regions]
if(length(regions) ==1){
return(sum(a > b) / length(a))
}else{
out <- vector()
for(i in brainrange(1,nrow(a))){
calc <- (b[i] / mean(as.numeric(na.exclude(a[i,]))))
if ( !is.na(calc) & calc > 1){
out <- c(out, sum(a[i,] > b[i]) / ncol(a))
}else{
out <- c(out, sum(a[i,] < b[i]) / ncol(a))
}
}
out <- as.list(out)
names(out) <- regions
return(out)
}
}
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