## Written by Mercedeh Movassagh <mercedeh@ds.dfci.harvard.edu>, Aug 2020
#' @importFrom stats quantile
NULL
#' threshSigInter Using shuffling threshold finds appropriate significant miRNA-mRNA correlation
#'
#' This function uses the sampCorRnaMirna shuffled output to determine an appropriate thershold
#' for significant mRNA and miRNA relationship of the dataset and shows all those with significant
#' relationships.
#' @param corr0 data.frame results of corMirnaRna function.
#' @param corrS vector of correlations, from the sampCorRnaMirna function.
#' @param pvalue The p value threshold to be used on the sampled data.
#' @return A dataframe of Significant mRNA and miRNA
#' @export
#' @keywords Signficance, Threshold
#' @examples
#' x <- threshSigInter(corr_0, outs, pvalue = 0.05)
threshSigInter <- function(corr0, corrS, pvalue = 0.05) {
threshold <- quantile(corrS, 1 - pvalue) # 5% default
sig_corrs <- corr0[corr0$value > threshold, ]
return(sig_corrs)
}
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