diff --git a/R/GatherPPIData.R b/R/GatherPPIData.R
index 54d4f131..27819364 100644
--- a/R/GatherPPIData.R
+++ b/R/GatherPPIData.R
@@ -498,7 +498,7 @@ GetGeneMANIA.edges <- function(gm.results.path,
 
     network_lines <- all_lines[start_line[1]:(end_line[1] - 1)]
 
-    edgetable <- read.table(
+    edgetable <- utils::read.table(
         text = network_lines,
         header = TRUE,
         stringsAsFactors = FALSE,
@@ -552,7 +552,7 @@ GetKinsub.edges <- function(kinasesubstrate.filename = "Kinase_Substrate_Dataset
     symbol.map = NULL) {
     nodes <- toupper(.map_nodes_with_symbol_map(gene.cccn.nodes, symbol.map))
 
-    kinasesubstrateraw <- read.table(
+    kinasesubstrateraw <- utils::read.table(
         kinasesubstrate.filename,
         header = TRUE,
         skip = 3,
diff --git a/R/MakeClusterList.R b/R/MakeClusterList.R
index 9a425876..ef96cab1 100644
--- a/R/MakeClusterList.R
+++ b/R/MakeClusterList.R
@@ -138,7 +138,7 @@ MakeClusterList <- function(ptmtable, keeplength = 2, toolong = 3.5, tsne_perple
         #  2.	For each cluster, set all PTM–PTM pairs in the cluster to 1 (indicating co-membership).
         #  3.	The final matrix for a method has 1 for PTM pairs co-clustered in that method; 0 otherwise.
 
-        co_membership_matrix <- function(clusters, all_ptms) {
+        co_membership_matrix <- function(clusters) {
             # 1. square matrix of all PTMs
             mat <- matrix(0,
                 nrow = length(PTMnames), ncol = length(PTMnames),
@@ -155,7 +155,7 @@ MakeClusterList <- function(ptmtable, keeplength = 2, toolong = 3.5, tsne_perple
             return(mat)
         }
 
-        adjacency_matrices <- purrr::map(clusters.list, co_membership_matrix, all_ptms = all_ptms)
+        adjacency_matrices <- purrr::map(clusters.list, co_membership_matrix)
 
         # Step 2: Sum the Co-Membership Matrices Across Methods
         adj.sum <- Reduce("+", adjacency_matrices) # values: 0 (never), 1, 2, 3 (co-clustered in all 3 methods)
diff --git a/R/MakeCorrelationNetwork.R b/R/MakeCorrelationNetwork.R
index aade533e..db3301c3 100644
--- a/R/MakeCorrelationNetwork.R
+++ b/R/MakeCorrelationNetwork.R
@@ -87,7 +87,7 @@ MakeCorrelationNetwork <- function(adj.consensus.matrix, ptm.correlation.matrix)
 
         # Sum correlations in one dimension, then the other dimension
         gene.cccn2 <- dplyr::summarise(
-            dplyr::group_by(gene.cccn, .data$Gene.Name),
+            dplyr::group_by(gene.cccn, Gene.Name),
             dplyr::across(
                 tidyselect::where(is.numeric),
                 ~ sum(.x, na.rm = TRUE)