diff --git a/R/IntegrativeAnalysis.R b/R/IntegrativeAnalysis.R
index ec4a2671..2fd54a24 100644
--- a/R/IntegrativeAnalysis.R
+++ b/R/IntegrativeAnalysis.R
@@ -1294,9 +1294,11 @@ addPeak2GeneLinks <- function(
   #Permuted Pval
   if(addPermutedPval){
     message("Performing Permuted P-values similar to Regner et al., 2021")
+    #set up variables to hold new data
+    permPval <- 0
+    correlation <- 0
     #Permute
     p <- o
-    o$PermPval <- 0
     for(i in seq_len(nperm)){
       message("Running Permutation ", i, " of ", nperm)
       idx <- sample(ncol(seATAC))
@@ -1304,10 +1306,12 @@ addPeak2GeneLinks <- function(
       p$TStat <- (p$Correlation / sqrt((1-p$Correlation^2)/(ncol(seATAC)-2))) #T-statistic P-value
       p$Pval <- 2*pt(-abs(p$TStat), ncol(seATAC) - 2)
       cdf <- ecdf(p$Pval)
-      o$PermPval <- o$PermPval + p$Pval
+      permPval <- permPval + p$Pval
+      correlation <- correlation + p$Correlation
     }
-    o$PermPval <- (o$PermPval / nperm) #Average
-    o$PermFDR <- pmin(ecdf(o$PermPval)(o$Pval) / ecdf(o$Pval)(o$Pval), 1)
+    out$PermCorrelation <- (correlation / nperm) #Average
+    out$PermPval <- (permPval / nperm) #Average
+    out$PermFDR <- pmin(ecdf(out$PermPval)(o$Pval) / ecdf(o$Pval)(o$Pval), 1)
   }
 
   #Save Group Matrices