diff --git a/R/tcplVarMat.R b/R/tcplVarMat.R
index c6caf1d..9562c89 100644
--- a/R/tcplVarMat.R
+++ b/R/tcplVarMat.R
@@ -9,6 +9,8 @@
 #' 
 #' @param dsstox_substance_id Integer, chemical ID values to subset on
 #' @param aeid Integer, assay endpoint ID values to subset on
+#' @param std.vars Character, standard set of matrices; use this parameter to 
+#' subset this list
 #' @param add.vars Character, mc4 or mc5 field(s) not included in the standard
 #' list to add additional matrices 
 #' @param flag Integer or Logical of length 1, passed to 
@@ -29,9 +31,9 @@
 #'  winning model.
 #'  \item "acc_verbose" -- The ACC for the winning model, with text describing
 #'  some situations.
-#'  \item "mc_hitc" -- The hit-call for the winning model in 
+#'  \item "hitc_mc" -- The hit-call for the winning model in 
 #'  multiple-concentration (mc) screening.
-#'  \item "sc_hitc" -- The hit-call in single concentration (sc) screening.
+#'  \item "hitc_sc" -- The hit-call in single concentration (sc) screening.
 #'  \item "zscore" -- The z-score based on the output from \code{tcplCytoPt}. 
 #'  The formula used for calculating the z-score is 
 #'  \eqn{-(\mathit{ac50} - \mathit{cyto\_pt})/\mathit{global\_mad}}
@@ -85,6 +87,7 @@
 #' dtxsid <- c("DTXSID4034653", "DTXSID2032683", "DTXSID6032358", 
 #' "DTXSID0032651", "DTXSID8034401")
 #' varmat <- tcplVarMat(aeid = aeids, dsstox_substance_id = dtxsid)
+#' varmat <- tcplVarMat(aeid = aeids, std.vars = c("ac50", "zscore"))
 #' varmat <- tcplVarMat(aeid = aeids, add.vars = c("m4id", "resp_max", "max_med"))
 #' 
 #' ## To save output to file
@@ -101,6 +104,7 @@
 
 tcplVarMat <- function(dsstox_substance_id = NULL,
                        aeid = NULL,
+                       std.vars = c("ac50", "ac50_verbose", "acc", "acc_verbose", "hitc_mc", "hitc_sc", "zscore"),
                        add.vars = NULL,
                        flag = TRUE,
                        cyto.pars = list()) {
@@ -117,9 +121,7 @@ tcplVarMat <- function(dsstox_substance_id = NULL,
 
   if (!all(add.vars %in% valid_var)) stop("Invald add.vars value(s).")
   
-  ac50str = ifelse(check_tcpl_db_schema(),"ac50","modl_ga")
-  
-  std.vars <- c(ac50str, paste0(ac50str, "_verbose"), "acc", "acc_verbose", "hitc", "hitc.y", "zscore")
+  std.vars[std.vars == "ac50"] = ifelse(check_tcpl_db_schema(),"ac50","modl_ga")
   vars <- c(std.vars, add.vars)
   
   ## Load all possibilities to create matrix dimensions
@@ -186,9 +188,11 @@ tcplVarMat <- function(dsstox_substance_id = NULL,
       var <- sub("_verbose", "", var)
       verbose = TRUE
     }
+    mc_var <- sub("\\_mc|\\_sc", "", var)
+    if (!mc_var %in% colnames(mc5)) stop(paste(mc_var, "is not a valid column in mc4 or mc5."))
     long_mc5 <- mc5 |> group_by(dsstox_substance_id,aenm,chnm) |> 
-      summarise(across(all_of(sub("\\.y", "", var)), mean)) |> filter(!is.na(dsstox_substance_id))
-    long_all <- long_mc5 |> full_join(long_sc2, by = c("dsstox_substance_id","aenm", "chnm"))
+      summarise(across(all_of(mc_var), mean)) |> filter(!is.na(dsstox_substance_id))
+    long_all <- long_mc5 |> full_join(long_sc2, suffix = c("_mc", "_sc"), by = c("dsstox_substance_id","aenm", "chnm"))
     long_res <- if (substr(var, 1, 2) == "ac") long_all |> 
       mutate("{var}" := case_when(is.na(get(var)) && hitc == 0 ~ 1e8, 
                                   is.na(get(var)) && hitc == 1 ~ 1e7, 
@@ -205,7 +209,7 @@ tcplVarMat <- function(dsstox_substance_id = NULL,
   
   mat_list <- lapply(vars, build_matrix)
 
-  names(mat_list) = c("ac50", "ac50_verbose", "acc", "acc_verbose", "mc_hitc", "sc_hitc", "zscore", add.vars)
+  names(mat_list) <- vars
   
   mat_list
   
diff --git a/man/tcplVarMat.Rd b/man/tcplVarMat.Rd
index df3f720..3de52ab 100644
--- a/man/tcplVarMat.Rd
+++ b/man/tcplVarMat.Rd
@@ -7,6 +7,8 @@
 tcplVarMat(
   dsstox_substance_id = NULL,
   aeid = NULL,
+  std.vars = c("ac50", "ac50_verbose", "acc", "acc_verbose", "hitc_mc", "hitc_sc",
+    "zscore"),
   add.vars = NULL,
   flag = TRUE,
   cyto.pars = list()
@@ -17,6 +19,9 @@ tcplVarMat(
 
 \item{aeid}{Integer, assay endpoint ID values to subset on}
 
+\item{std.vars}{Character, standard set of matrices; use this parameter to 
+subset this list}
+
 \item{add.vars}{Character, mc4 or mc5 field(s) not included in the standard
 list to add additional matrices}
 
@@ -47,9 +52,9 @@ for different parameters. The standard list of matrices returned includes:
  winning model.
  \item "acc_verbose" -- The ACC for the winning model, with text describing
  some situations.
- \item "mc_hitc" -- The hit-call for the winning model in 
+ \item "hitc_mc" -- The hit-call for the winning model in 
  multiple-concentration (mc) screening.
- \item "sc_hitc" -- The hit-call in single concentration (sc) screening.
+ \item "hitc_sc" -- The hit-call in single concentration (sc) screening.
  \item "zscore" -- The z-score based on the output from \code{tcplCytoPt}. 
  The formula used for calculating the z-score is 
  \eqn{-(\mathit{ac50} - \mathit{cyto\_pt})/\mathit{global\_mad}}
@@ -99,6 +104,7 @@ aeids <- c(80)
 dtxsid <- c("DTXSID4034653", "DTXSID2032683", "DTXSID6032358", 
 "DTXSID0032651", "DTXSID8034401")
 varmat <- tcplVarMat(aeid = aeids, dsstox_substance_id = dtxsid)
+varmat <- tcplVarMat(aeid = aeids, std.vars = c("ac50", "zscore"))
 varmat <- tcplVarMat(aeid = aeids, add.vars = c("m4id", "resp_max", "max_med"))
 
 ## To save output to file