diff --git a/R/bayesiannetworkanalysis.R b/R/bayesiannetworkanalysis.R
index 509a4c0..94e233f 100644
--- a/R/bayesiannetworkanalysis.R
+++ b/R/bayesiannetworkanalysis.R
@@ -41,7 +41,7 @@ BayesianNetworkAnalysis <- function(jaspResults, dataset, options) {
   mainContainer <- jaspResults[["mainContainer"]]
   if (is.null(mainContainer)) {
     mainContainer <- createJaspContainer(dependencies = c("variables", "groupingVariable", "estimator",
-                                                          "burnin", "iter", "gprior", "dfprior"))
+                                                          "burnin", "iter", "gprior", "dfprior", "setSeed", "seed"))
     jaspResults[["mainContainer"]] <- mainContainer
   }
   .bayesianNetworkAnalysisMainTableMeta(mainContainer, dataset, options)
diff --git a/R/networkanalysis.R b/R/networkanalysis.R
index 814440f..a02aeff 100644
--- a/R/networkanalysis.R
+++ b/R/networkanalysis.R
@@ -95,8 +95,11 @@ NetworkAnalysis <- function(jaspResults, dataset, options) {
 
     # check if data must be binarized
     if (options[["estimator"]] %in% c("isingFit", "isingSampler")) {
-      idx <- colnames(dataset) != options[["groupingVariable"]]
-      dataset[idx] <- bootnet::binarize(dataset[idx], split = options[["split"]], verbose = FALSE, removeNArows = FALSE)
+
+      for (i in seq_along(dataset)) {
+        idx <- colnames(dataset[[i]]) != options[["groupingVariable"]]
+        dataset[[i]][idx] <- bootnet::binarize(dataset[[i]][idx], split = options[["split"]], verbose = FALSE, removeNArows = FALSE)
+      }
 
       if (options[["estimator"]] == "isingFit") {
         # required check since isingFit removes these variables from the analyses