diff --git a/NEWS.md b/NEWS.md
index 823828d..3f0304a 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -2,4 +2,8 @@
 
 ## plotMetadata
 
-* Improved metadata selection, validation, and run logging for `plotMetadata()` (#95).
\ No newline at end of file
+* Improved metadata selection, validation, and run logging for `plotMetadata()` (#95).
+
+## heatmapSC
+
+* Add `sample.name.column` to select the metadata column used for sample filtering, defaulting to `orig.ident` (#100).
\ No newline at end of file
diff --git a/R/Heatmap.R b/R/Heatmap.R
index 0c50340..f86a775 100755
--- a/R/Heatmap.R
+++ b/R/Heatmap.R
@@ -5,6 +5,8 @@
 #'
 #' @param object Seurat-class object
 #' @param sample.names Sample names
+#' @param sample.name.column Metadata column containing sample names. Blank
+#'   values default to "orig.ident".
 #' @param metadata Metadata column to plot
 #' @param transcripts Transcripts to plot
 #' @param use.assay Assay to use for transcript expression values. Choices are
@@ -82,7 +84,8 @@ heatmapSC <- function(object,
                       trim.outliers = TRUE,
                       trim.outliers.percentage = 0.01,
                       order.heatmap.rows = FALSE,
-                      row.order = c()) {
+                      row.order = c(),
+                      sample.name.column = "orig.ident") {
   
   #### Functions ####
   n <- 2e3
@@ -177,8 +180,12 @@ heatmapSC <- function(object,
     leg.breaks = sapply(leg.breaks, signif, 4)
     
     #Run cluster method:
-    hc = hclust(dist(t(dat)), method = "complete")
-    hcrow = hclust(dist(dat), method = "complete")
+    if (ncol(dat) > 1) {
+      hc = hclust(dist(t(dat)), method = "complete")
+    }
+    if (nrow(dat) > 1) {
+      hcrow = hclust(dist(dat), method = "complete")
+    }
     
     if (clus.col == TRUE) {
       .sortHClust <-
@@ -189,7 +196,7 @@ heatmapSC <- function(object,
         as.hclust(dendsort(as.dendrogram(...)))
     }
     
-    if (clus.row == TRUE) {
+    if (clus.row == TRUE && nrow(dat) > 1) {
       row.clus <- .sortHClust(hcrow)
     } else {
       row.clus = FALSE
@@ -218,7 +225,7 @@ heatmapSC <- function(object,
       main = plot.title,
       clustering_method = "complete",
       cluster_rows = row.clus,
-      cluster_cols = clus.col,
+      cluster_cols = clus.col && ncol(dat) > 1,
       clustering_distance_rows = "euclidean",
       clustering_distance_cols = "euclidean",
       annotation_col = annotation.col,
@@ -241,7 +248,6 @@ heatmapSC <- function(object,
   # Select samples to include
   samples.to.include = sample.names
   samples.to.include <- samples.to.include[samples.to.include != ""]
-  samples.to.include <- gsub("-", "_", samples.to.include)
   
   #Error messaging for metadata 
   
@@ -254,65 +260,76 @@ heatmapSC <- function(object,
     metadata <- metadata[!grepl('Barcode', metadata, ignore.case=TRUE)]
   }
   
-  #Clean up transcript names and print missing genes:
-  transcripts = gsub(" ", "", transcripts)
-  
-  l1 <- length(transcripts)
-  p1 <- length(proteins)
+  # Clean up and validate transcript and protein names.
+  if (is.null(transcripts)) {
+    transcripts <- character()
+  }
+  if (is.null(proteins)) {
+    proteins <- character()
+  }
+  transcripts <- gsub(" ", "", transcripts)
+  proteins <- gsub(" ", "", proteins)
+  transcripts <- transcripts[nzchar(transcripts)]
+  proteins <- proteins[nzchar(proteins)]
   
-  if(l1 + p1 == 0){
+  if (length(transcripts) + length(proteins) == 0) {
     stop(sprintf("At least 1 transcript and/or protein is needed for plotting"))
   }
   
   dups <- transcripts[duplicated(transcripts)]
   transcripts <- transcripts[!duplicated(transcripts)]
-  
-  
-  l2 <- length(transcripts)
-  sprintf("There are %s total unique genes/proteins in the dataset", l2)
-  if (l1 > l2) {
+  if (length(dups) > 0) {
     warning(sprintf("\n\nThe following duplicate genes were removed: %s",
                     dups))
   }
   
-  if (transcripts[1] != "") {
-    missing.genes = setdiff(transcripts, rownames(object$SCT@scale.data))
-    if (length(missing.genes) > 0) {
-      print(paste("missing genes:", missing.genes))
-    }
+  if (!use.assay %in% c("SCT", "Harmony")) {
+    stop("use.assay must be either 'SCT' or 'Harmony'.")
   }
-  
-  #missing.genes <- transcripts[!transcripts %in% rownames(object)]
-  l3 <- length(missing.genes)
-  missing.genes <- paste(shQuote(missing.genes), collapse = ", ")
-  if (l3 == l2) {
-    stop("No genes listed are found in dataset.")
-  }
-  if (l3 > 0) {
-    warning(
-      sprintf(
-        "There are %s gene(s) absent from dataset:
-            %s. Possible reasons are that gene is not official
-            gene symbol or gene is not highly expressed and
-            has been filtered.\n ",
-        l3,
-        missing.genes
-      )
+  if (length(transcripts) > 0 && !use.assay %in% names(object@assays)) {
+    stop("Transcript assay '", use.assay, "' was not found in the Seurat object.")
+  }
+  transcript.data <- object@assays[[use.assay]]@scale.data
+  missing.genes <- setdiff(transcripts, rownames(transcript.data))
+  if (length(missing.genes) > 0) {
+    missing.transcript.message <- paste0(
+      "There are ", length(missing.genes), " gene(s) absent from dataset: ",
+      paste(shQuote(missing.genes), collapse = ", "),
+      ". Possible reasons are that gene is not official gene symbol or gene is ",
+      "not highly expressed and has been filtered."
     )
+    message(missing.transcript.message)
+    warning(missing.transcript.message)
   }
-  
-  transcripts <- transcripts[transcripts %in% rownames(object)]
-  
-  #Clean up protein names and print missing proteins:
-  if (!is.null(object@assays$Protein)) {
-    proteins = gsub(" ", "", proteins)
-    if (proteins[1] != "") {
-      protmiss = setdiff(proteins, rownames(object$Protein@scale.data))
-      if (length(protmiss) > 0) {
-        sprintf("missing proteins: %s", protmiss)
-      }
+  transcripts <- transcripts[transcripts %in% rownames(transcript.data)]
+  if (length(transcripts) > 0) {
+    message("Transcripts found in ", use.assay, ": ",
+            paste(transcripts, collapse = ", "))
+  }
+
+  if (length(proteins) > 0 && !"Protein" %in% names(object@assays)) {
+    stop("Protein assay was not found.")
+  }
+
+  if (length(proteins) > 0) {
+    missing.proteins <- setdiff(proteins, rownames(object$Protein@scale.data))
+    if (length(missing.proteins) > 0) {
+      missing.protein.message <- paste0(
+        "Proteins not found in Protein assay: ",
+        paste(missing.proteins, collapse = ", "), ". They will be excluded."
+      )
+      message(missing.protein.message)
+      warning(missing.protein.message)
+    }
+    proteins <- proteins[proteins %in% rownames(object$Protein@scale.data)]
+    if (length(proteins) > 0) {
+      message("Proteins found in Protein assay: ",
+              paste(proteins, collapse = ", "))
     }
-    proteins = proteins[proteins %in% rownames(object$Protein@scale.data)]
+  }
+
+  if (length(transcripts) + length(proteins) == 0) {
+    stop("No requested transcripts or proteins were found in the selected assays.")
   }
   
   #Error messaging for protein annotation tracks:
@@ -325,24 +342,13 @@ heatmapSC <- function(object,
   #collect transcript expression data from SCT / Harmony slot
   df.mat1 = NULL
   if (length(transcripts) > 0) {
-    if (length(transcripts) == 1) {
-      if(use.assay == 'SCT'){
-        df.mat1 <-
-          vector(mode = "numeric",
-                 length = length(object$SCT@scale.data[transcripts,]))
-        df.mat1 <- object$SCT@scale.data[transcripts,]
-      } else if (use.assay == 'Harmony'){
-        df.mat1 <-
-          vector(mode = "numeric",
-                 length = length(object$Harmony@scale.data[transcripts,]))
-        df.mat1 <- object$Harmony@scale.data[transcripts,]
-        }
-    } else {
-      if(use.assay == 'SCT'){
-        df.mat1 <- as.matrix(object$SCT@scale.data[transcripts,])
-      } else if (use.assay == 'Harmony'){
-        df.mat1 <- as.matrix(object$Harmony@scale.data[transcripts,])
-        }
+    if(use.assay == 'SCT'){
+      df.mat1 <- object$SCT@scale.data[transcripts, , drop = FALSE]
+    } else if (use.assay == 'Harmony'){
+      df.mat1 <- object$Harmony@scale.data[transcripts, , drop = FALSE]
+    }
+    if (!is.null(df.mat1)) {
+      rownames(df.mat1) <- transcripts
     }
   }
   
@@ -350,15 +356,9 @@ heatmapSC <- function(object,
   df.mat2 = NULL
   if (!is.null(object@assays$Protein)) {
     if (length(proteins) > 0) {
-      if (length(proteins) == 1) {
-        df.mat2 <-
-          vector(mode = "numeric",
-                 length = length(object$Protein@scale.data[proteins,]))
-        df.mat2 <- object$Protein@scale.data[proteins,]
-        protname <- paste0(proteins, "_Prot")
-      } else {
-        df.mat2 <- as.matrix(object$Protein@scale.data[proteins,])
-        protname <- paste0(proteins, "_Prot")
+      df.mat2 <- object$Protein@scale.data[proteins, , drop = FALSE]
+      protname <- paste0(proteins, "_Prot")
+      if (!is.null(df.mat2)) {
         rownames(df.mat2) <- protname
       }
     }
@@ -366,15 +366,7 @@ heatmapSC <- function(object,
   
   #Put together transcript and protein data
   df.mat <- rbind(df.mat1, df.mat2)
-  if (!is.null(df.mat1)) {
-    rownames(df.mat)[rownames(df.mat) == "df.mat1"] <- transcripts
-  }
-  
-  if (!is.null(df.mat2)) {
-    rownames(df.mat)[rownames(df.mat) == "df.mat2"] <- protname
-  }
-  
-  df.mat <- df.mat[sort(rownames(df.mat)),]
+  df.mat <- df.mat[sort(rownames(df.mat)), , drop = FALSE]
   
   #Set row order to specific genes/proteins
   if (order.heatmap.rows == TRUE) {
@@ -386,11 +378,42 @@ heatmapSC <- function(object,
     cluster.rows <- TRUE
   }
   
-  metadata <- sub("orig_ident", "orig.ident", metadata)
+  if (is.null(sample.name.column) ||
+      (is.character(sample.name.column) &&
+       (length(sample.name.column) == 0 ||
+        (length(sample.name.column) == 1 &&
+         !is.na(sample.name.column) &&
+         !nzchar(trimws(sample.name.column)))))) {
+    sample.name.column <- "orig.ident"
+  }
+
+  if (length(sample.name.column) != 1 ||
+      !is.character(sample.name.column) ||
+      is.na(sample.name.column) ||
+      !nzchar(trimws(sample.name.column))) {
+    stop("sample.name.column must be a single, non-empty metadata column name.")
+  }
+
+  if (!sample.name.column %in% colnames(object@meta.data)) {
+    if (identical(sample.name.column, "orig.ident")) {
+      warning("Default sample name column 'orig.ident' was not found in Seurat metadata.")
+    }
+    stop("Could not find requested sample name column: ", sample.name.column)
+  }
   
   #Set up annotation track:
-  metadata.table <- object@meta.data %>%
-    dplyr::filter(orig.ident %in% samples.to.include)
+  metadata.table <- object@meta.data[
+    object@meta.data[[sample.name.column]] %in% samples.to.include,
+    ,
+    drop = FALSE
+  ]
+
+  if (nrow(metadata.table) == 0) {
+    stop(
+      "No cells matched the requested sample names in metadata column: ",
+      sample.name.column
+    )
+  }
   
   annot <- metadata.table %>% select(all_of(metadata))
   a = dim(annot)[2] - 1
@@ -433,10 +456,10 @@ heatmapSC <- function(object,
   #Arrange columns by metadata tracks:
   if (arrange.by.metadata == TRUE) {
     annot <- annot %>% arrange(across(all_of(colnames(annot)))) 
-    df.mat <- df.mat[, match(rownames(annot), colnames(df.mat))]
+    df.mat <- df.mat[, match(rownames(annot), colnames(df.mat)), drop = FALSE]
     df.mat <-
       df.mat[, apply(df.mat, 2, function(x)
-        ! any(is.na(x)))]
+        ! any(is.na(x))), drop = FALSE]
     cluster.cols = FALSE
   } else {
     cluster.cols = TRUE
@@ -498,7 +521,7 @@ heatmapSC <- function(object,
   # Apply scaling to data (optional)
   if (scale.data == TRUE) {
     tmean.scale = t(scale(t(df.mat)))
-    tmean.scale = tmean.scale[is.finite(rowSums(tmean.scale)),]
+    tmean.scale = tmean.scale[is.finite(rowSums(tmean.scale)), , drop = FALSE]
   } else {
     tmean.scale = df.mat
   }
diff --git a/man/heatmapSC.Rd b/man/heatmapSC.Rd
index 351c608..89abb41 100644
--- a/man/heatmapSC.Rd
+++ b/man/heatmapSC.Rd
@@ -28,7 +28,8 @@ heatmapSC(
   trim.outliers = TRUE,
   trim.outliers.percentage = 0.01,
   order.heatmap.rows = FALSE,
-  row.order = c()
+  row.order = c(),
+  sample.name.column = "orig.ident"
 )
 }
 \arguments{
@@ -83,6 +84,9 @@ heatmapSC(
 
 \item{row.order}{Gene vector to set row order. If empty, use cluster order
 (default is empty vector)}
+
+\item{sample.name.column}{Metadata column containing sample names. Blank
+values default to "orig.ident". Sample values are matched exactly.}
 }
 \value{
 This function returns a heatmap plot and the data underlying the
diff --git a/tests/testthat/test-Heatmap.R b/tests/testthat/test-Heatmap.R
index 087db72..76c49a4 100755
--- a/tests/testthat/test-Heatmap.R
+++ b/tests/testthat/test-Heatmap.R
@@ -29,19 +29,194 @@ test_that("Heatmap scaled vs unscaled", {
 
 })
 
+test_that("Heatmap uses orig.ident without renaming metadata columns", {
+  cr.object <- getParamHM("Chariou")
+  metadata.names <- colnames(cr.object$object@meta.data)
+  cr.object$metadata <- "orig.ident"
+
+  output <- do.call(heatmapSC, cr.object)
+
+  expect_setequal(names(output), c("plots", "data"))
+  expect_identical(colnames(cr.object$object@meta.data), metadata.names)
+  expect_true("orig.ident" %in% colnames(cr.object$object@meta.data))
+  expect_false("orig_ident" %in% colnames(cr.object$object@meta.data))
+})
+
+test_that("Heatmap supports a custom sample name column", {
+  cr.object <- getParamHM("Chariou")
+  cr.object$object@meta.data[["sample.name_1.2"]] <-
+    cr.object$object@meta.data[["orig.ident"]]
+  metadata.names <- colnames(cr.object$object@meta.data)
+  cr.object$sample.name.column <- "sample.name_1.2"
+  selected.sample <- unique(cr.object$object@meta.data[["sample.name_1.2"]])[[1]]
+  cr.object$sample.names <- selected.sample
+  expected.cells <- rownames(cr.object$object@meta.data)[
+    cr.object$object@meta.data[["sample.name_1.2"]] == selected.sample
+  ]
+
+  output <- do.call(heatmapSC, cr.object)
+
+  expect_setequal(names(output), c("plots", "data"))
+  expect_setequal(colnames(output$data)[-1], expected.cells)
+  expect_identical(colnames(cr.object$object@meta.data), metadata.names)
+})
+
+test_that("Heatmap preserves punctuation in sample names", {
+  cr.object <- getParamHM("Chariou")
+  sample.column <- "sample.name_1.2"
+  sample.values <- rep(
+    c("sample.1-A", "sample.2-B"),
+    length.out = nrow(cr.object$object@meta.data)
+  )
+  cr.object$object@meta.data[[sample.column]] <- sample.values
+  metadata.names <- colnames(cr.object$object@meta.data)
+  cr.object$sample.name.column <- sample.column
+  cr.object$sample.names <- "sample.1-A"
+  expected.cells <- rownames(cr.object$object@meta.data)[
+    cr.object$object@meta.data[[sample.column]] == "sample.1-A"
+  ]
+
+  output <- do.call(heatmapSC, cr.object)
+
+  expect_setequal(colnames(output$data)[-1], expected.cells)
+  expect_identical(colnames(cr.object$object@meta.data), metadata.names)
+})
+
+test_that("Heatmap defaults blank sample name columns to orig.ident", {
+  cr.object <- getParamHM("Chariou")
+  cr.object$sample.name.column <- ""
+
+  output <- do.call(heatmapSC, cr.object)
+
+  expect_setequal(names(output), c("plots", "data"))
+})
+
+test_that("Heatmap warns when the default sample name column is absent", {
+  cr.object <- getParamHM("Chariou")
+  cr.object$sample.name.column <- ""
+  cr.object$object@meta.data[["orig.ident"]] <- NULL
+
+  expect_warning(
+    expect_error(
+      do.call(heatmapSC, cr.object),
+      "Could not find requested sample name column: orig.ident"
+    ),
+    "Default sample name column 'orig.ident' was not found in Seurat metadata."
+  )
+})
+
+test_that("Heatmap rejects invalid sample name columns", {
+  cr.object <- getParamHM("Chariou")
+  cr.object$sample.name.column <- c("orig.ident", "Phase")
+
+  expect_error(
+    do.call(heatmapSC, cr.object),
+    "sample.name.column must be a single, non-empty metadata column name."
+  )
+
+  cr.object$sample.name.column <- "not_a_metadata_column"
+  expect_error(
+    do.call(heatmapSC, cr.object),
+    "Could not find requested sample name column: not_a_metadata_column"
+  )
+})
+
+test_that("Heatmap errors clearly when no cells match selected samples", {
+  cr.object <- getParamHM("Chariou")
+  cr.object$sample.names <- "not_a_sample"
+
+  expect_error(
+    do.call(heatmapSC, cr.object),
+    "No cells matched the requested sample names in metadata column: orig.ident"
+  )
+})
+
+test_that("Heatmap supports a single transcript", {
+  cr.object <- getParamHM("Chariou")
+  cr.object$transcripts <- cr.object$transcripts[[1]]
+  cr.object$add.gene.or.protein <- FALSE
+  cr.object$rna.annotations <- NULL
+
+  output <- do.call(heatmapSC, cr.object)
+
+  expect_identical(output$data$gene, cr.object$transcripts)
+})
+
+test_that("Heatmap supports a single protein", {
+  cr.object <- getParamHM("nsclc-multi")
+  cr.object$transcripts <- cr.object$transcripts[[1]]
+  cr.object$proteins <- cr.object$proteins[[1]]
+  cr.object$add.gene.or.protein <- FALSE
+  cr.object$rna.annotations <- NULL
+  cr.object$protein.annotations <- NULL
+
+  output <- do.call(heatmapSC, cr.object)
+
+  expect_setequal(
+    output$data$gene,
+    c(cr.object$transcripts, paste0(cr.object$proteins, "_Prot"))
+  )
+})
+
 test_that("Heatmap run with bad gene name", {
   cr.object <- getParamHM("TEC")
 
   #Spike in with bad gene name
   cr.object$transcripts <- c("badgene", cr.object$transcripts)
+  missing.transcript.message <- paste0(
+    "There are 1 gene(s) absent from dataset: 'badgene'. Possible reasons are ",
+    "that gene is not official gene symbol or gene is not highly expressed and ",
+    "has been filtered."
+  )
+
+  expect_warning(
+    expect_message(
+      do.call(heatmapSC, cr.object),
+      missing.transcript.message,
+      fixed = TRUE
+    ),
+    missing.transcript.message,
+    fixed = TRUE
+  )
+})
 
-  expect_warning(do.call(heatmapSC, cr.object), "^There are")
+test_that("Heatmap reports missing proteins and retains available proteins", {
+  cr.object <- getParamHM("nsclc-multi")
+  cr.object$proteins <- c("CD3", "not_a_protein")
+  cr.object$protein.annotations <- NULL
+
+  expect_warning(
+    expect_message(
+      output <- do.call(heatmapSC, cr.object),
+      "Proteins not found in Protein assay: not_a_protein. They will be excluded."
+    ),
+    "Proteins not found in Protein assay: not_a_protein. They will be excluded."
+  )
+
+  expect_true("CD3_Prot" %in% output$data$gene)
+  expect_false("not_a_protein_Prot" %in% output$data$gene)
+})
+
+test_that("Heatmap requires the selected transcript assay", {
+  cr.object <- getParamHM("TEC")
+  cr.object$use.assay <- "Harmony"
 
-  #Actual warning:
-  #There are 1 gene(s) absent from dataset:'badgene'.
-  #Possible reasons are that gene is not official gene symbol
-  #or gene is not highly expressed and has been filtered.
+  expect_error(
+    do.call(heatmapSC, cr.object),
+    "Transcript assay 'Harmony' was not found in the Seurat object."
+  )
+})
 
+test_that("Heatmap requires a CITE-seq Protein assay for proteins", {
+  cr.object <- getParamHM("TEC")
+  cr.object$transcripts <- character()
+  cr.object$proteins <- "CD3"
+
+  expect_error(
+    do.call(heatmapSC, cr.object),
+    "Protein assay was not found.",
+    fixed = TRUE
+  )
 })
 
 test_that("Heatmap run with duplicate gene names", {
@@ -59,8 +234,23 @@ test_that("Heatmap run with error for missing all genes", {
   cr.object <- getParamHM("TEC")
   cr.object$transcripts <-
     c("APOE", "ARG1", "CD38", "CD3D", "CD3E", "CD3G")
-  expect_error(do.call(heatmapSC, cr.object),
-               "No genes listed are found in dataset.")
+  missing.transcript.message <- paste0(
+    "There are 6 gene(s) absent from dataset: 'APOE', 'ARG1', 'CD38', 'CD3D', ",
+    "'CD3E', 'CD3G'. Possible reasons are that gene is not official gene symbol ",
+    "or gene is not highly expressed and has been filtered."
+  )
+  expect_warning(
+    expect_message(
+      expect_error(
+        do.call(heatmapSC, cr.object),
+        "No requested transcripts or proteins were found in the selected assays."
+      ),
+      missing.transcript.message,
+      fixed = TRUE
+    ),
+    missing.transcript.message,
+    fixed = TRUE
+  )
 
 })
 
diff --git a/vignettes/SCWorkflow-Visualizations.Rmd b/vignettes/SCWorkflow-Visualizations.Rmd
index 4ec13ab..406a683 100644
--- a/vignettes/SCWorkflow-Visualizations.Rmd
+++ b/vignettes/SCWorkflow-Visualizations.Rmd
@@ -225,6 +225,7 @@ The heatmap is produced by a package called ComplexHeatmap [3] and presents the
 FigOut=heatmapSC(
           object=Anno_SO$object,
           sample.names=c("PBS","ENT","NHSIL12","Combo","CD8dep" ),
+          sample.name.column = "orig.ident",
           metadata="SCT_snn_res.0.4",
           transcripts=c("Cd163","Cd38","Itgam","Cd4","Cd8a","Pdcd1","Ctla4"),
           use.assay = "SCT",