diff --git a/.Rbuildignore b/.Rbuildignore
index c2c230f..655c812 100644
--- a/.Rbuildignore
+++ b/.Rbuildignore
@@ -4,4 +4,10 @@
 ^README\.Rmd$
 ^\.github$
 ^data-raw$
+^dcs04_data$
+^dcs04_data/.*$
 ^codecov\.yml$
+^\.Rhistory$
+^\.Rdata$
+^\.httr-oauth$
+^\.DS_Store$
diff --git a/.gitignore b/.gitignore
index 8b78a3a..1fb1ed6 100644
--- a/.gitignore
+++ b/.gitignore
@@ -4,4 +4,5 @@
 .Rdata
 .httr-oauth
 .DS_Store
+dcs04_data
 inst/doc
diff --git a/DESCRIPTION b/DESCRIPTION
index 1f9f199..9d4781e 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,7 +1,7 @@
 Package: qsvaR
 Title: Generate Quality Surrogate Variable Analysis for Degradation Correction
-Version: 1.9.0
-Date: 2024-05-03
+Version: 1.9.1
+Date: 2024-09-16
 Authors@R: 
     c(
     person("Joshua", "Stolz", email = "jstolz80@gmail.com",
@@ -25,7 +25,7 @@ biocViews: Software, WorkflowStep, Normalization, BiologicalQuestion,
     DifferentialExpression, Sequencing, Coverage
 Encoding: UTF-8
 Roxygen: list(markdown = TRUE)
-RoxygenNote: 7.3.0
+RoxygenNote: 7.3.2
 Suggests: 
     BiocFileCache,
     BiocStyle,
diff --git a/NAMESPACE b/NAMESPACE
index f492de8..efd1f82 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -1,13 +1,14 @@
 # Generated by roxygen2: do not edit by hand
 
 export(DEqual)
-export(check_tx_names)
 export(getDegTx)
 export(getPCs)
 export(get_qsvs)
 export(k_qsvs)
+export(normalize_tx_names)
 export(qSVA)
 export(select_transcripts)
+export(which_tx_names)
 import(SummarizedExperiment)
 import(ggplot2)
 import(rlang)
diff --git a/R/DEqual.R b/R/DEqual.R
index dd535d2..5027cc3 100644
--- a/R/DEqual.R
+++ b/R/DEqual.R
@@ -8,11 +8,22 @@
 #' <https://doi.org/10.1016/j.neuron.2019.05.013>. This function compares your
 #' t-statistics of interest computed on transcripts against the
 #' t-statistics from degradation time adjusting for the six brain regions from
-#' degradation experiment data used for determining `covComb_tx_deg`.
+#' degradation experiment data used for determining `rse_tx`.
 #'
-#' @param DE a `data.frame()` with one column containing the t-statistics from
-#' Differential Expression, typically generated with `limma::topTable()`.
-#' The `rownames(DE)` should be transcript GENCODE IDs.
+#' @param DE a `data.frame()` with a column "t" containing the t-statistics
+#' from Differential Expression, typically generated with `limma::topTable()`.
+#' `rownames(DE)` must have transcript Ensembl/Gencode IDs.
+#' @param deg_tstats an optional `data.frame()` with a column "t" containing
+#' t-statistics resulted from a degradation experiment. Default is the
+#' internal `qsvaR::degradation_tstats` from the package authors.
+#' @param show.legend logical (default TRUE) to show legend in the plot
+#' @param show.cor specify where to show the correlation value. Can be one of
+#' "caption", "corner-top", "corner-bottom", or "none".
+#' @param font.size numeric value to set the base font size of the plot
+#' @param cor.size numeric (default font.size/2) to set the font size for the
+#' correlation text
+#' @param cor.label character (default "cor: ") to set the text preceding the
+#'  correlation value
 #'
 #' @return a `ggplot` object of the DE t-statistic vs
 #' the DE statistic from degradation
@@ -36,47 +47,71 @@
 #'
 #' ## Create the DEqual plot
 #' DEqual(random_de)
-DEqual <- function(DE) {
+DEqual <- function(DE, deg_tstats = qsvaR::degradation_tstats, show.legend = TRUE,
+                        show.cor = c('caption','corner-top','corner-bottom','none'),
+                        font.size = 12,  cor.size = font.size/2, cor.label = 'cor: ') {
     ## For R CMD check
     DE_t <- degradation_t <- NULL
-
+    show.cor=rlang::arg_match(show.cor)
     ## Check input
-    # stopifnot("t" %in% colnames(DE))
-    # stopifnot(!is.null(rownames(DE)))
-    
-    # Check if input is a dataframe
-    if (!is.data.frame(DE)) { 
-      stop("The input to DEqual is not a dataframe.", call. = FALSE) 
+    if (!is.data.frame(DE)) {
+      stop("The input to DEqual is not a dataframe.", call. = FALSE)
       }
-
     # Check if 't' is in the column names of DE
     if (!("t" %in% colnames(DE))) {
         stop("'t' is not a column in 'DE'.", call. = FALSE)
       }
-    
     # Check if DE has non-null row names
     if (is.null(rownames(DE))) {
         stop("Row names of 'DE' are NULL.", call. = FALSE)
-      }
-    
+    }
+    if (!missing(deg_tstats)) {
+        if (!is.data.frame(deg_tstats)) {
+            stop("The 'deg_tstats' parameter is not a dataframe.", call. = FALSE)
+        }
+        if (!("t" %in% colnames(deg_tstats))) {
+            stop("'t' is not a column in 'deg_tstats'.", call. = FALSE)
+        }
+        if (is.null(rownames(deg_tstats))) {
+            stop("Row names of 'deg_tstats' are NULL.", call. = FALSE)
+        }
+        if (!all(grepl("^ENST\\d+", rownames(deg_tstats)))) {
+            stop("The row names of 'deg_tstats' must be ENSEMBL or Gencode IDs (ENST...)", call. = FALSE)
+        }
+    }
+
     ## Locate common transcripts
-    deg_tstats = qsvaR::degradation_tstats
-    rownames(deg_tstats) = check_tx_names(rownames(DE),rownames(qsvaR::degradation_tstats),'rownames(DE)','qsvaR::degradation_tstats')
-    common = intersect(rownames(deg_tstats), rownames(DE))
-    
+    whichTx <- which_tx_names(rownames(DE),rownames(deg_tstats))
+    common = qsvaR::normalize_tx_names(rownames(DE)[whichTx])
     stopifnot(length(common) > 0)
-    
+    rownames(deg_tstats) <- qsvaR::normalize_tx_names(rownames(deg_tstats))
     ## Create dataframe with common transcripts
     common_data <- data.frame(
-        degradation_t = deg_tstats$t[match(common, rownames(deg_tstats))],
-        DE_t = DE$t[match(common, rownames(DE))]
+        degradation_t = deg_tstats[common, "t"],
+        DE_t = DE[whichTx, "t"]
     )
+    cor_val <- signif(cor(common_data[, 1], common_data[, 2]), 2)
     p <- ggplot(common_data, aes(x = DE_t, y = degradation_t)) +
         xlab("DE t-statistic") +
         ylab("Degradation t-statistic") +
-        geom_bin2d(bins = 70) +
+        geom_bin2d(bins = 70, show.legend = show.legend) +
         scale_fill_continuous(type = "viridis") +
         theme_bw() +
-        labs(caption = paste0("correlation: ", signif(cor(common_data[, 1], common_data[, 2]), 2)))
+        theme(text = element_text(size = font.size))
+        # labs(caption = paste0("correlation: ", cor_val)
+    if (show.cor != 'none') {
+      switch(show.cor,
+        'caption' = {
+          p <- p + labs(caption = paste0(cor.label, cor_val))
+        },
+        'corner-top' = {
+          p <- p + annotate("text", x = max(common_data$DE_t), y = max(common_data$degradation_t),
+                            label = paste0(cor.label, cor_val), size = cor.size, hjust = 1, vjust = 1)
+        },
+        'corner-bottom' = {
+          p <- p + annotate("text", x = max(common_data$DE_t), y = min(common_data$degradation_t),
+                            label = paste0(cor.label, cor_val), size = cor.size, hjust = 1, vjust = 0)
+        })
+    }
     return(p)
 }
diff --git a/R/covComb_tx_deg-data.R b/R/covComb_tx_deg-data.R
deleted file mode 100644
index 509b498..0000000
--- a/R/covComb_tx_deg-data.R
+++ /dev/null
@@ -1,14 +0,0 @@
-#' RSE object of RNA-seq data that serves as output for degradation analysis
-#'
-#' This data was generated from an experiment using degraded RNA-seq samples
-#' post-mortem brain tissue. The transcripts included are the result of the qsva
-#' expanded framework study and will be used to remove the effect of degradation
-#' in bulk RNA-seq data.
-#'
-#'
-#' @name covComb_tx_deg
-#' @docType data
-#' @format A [RangedSummarizedExperiment-class][SummarizedExperiment::RangedSummarizedExperiment-class]
-#' @keywords datasets
-#' @seealso [getPCs] [k_qsvs] [getDegTx]
-NULL
diff --git a/R/degradation_tstats-data.R b/R/degradation_tstats-data.R
index cb794de..514f888 100644
--- a/R/degradation_tstats-data.R
+++ b/R/degradation_tstats-data.R
@@ -1,10 +1,10 @@
 #' Degradation time t-statistics
 #'
-#' These t-statistics are derived from the same data that was used for
-#' [covComb_tx_deg]. They are the results from main model where we determined
-#' the relationship with degradation time adjusting for the brain region (so
-#' parallel degradation effects across brain regions). They are used for
-#' plotting in `DEqual()`.
+#' These t-statistics are derived from the degradation timepoints data
+#' built into qsvaR. They are the results from multiple models where
+#' we determined the association of transcripts with degradation time
+#' adjusting for brain region (so parallel degradation effects across
+#' brain regions). They are used for plotting in `DEqual()`.
 #'
 #' @name degradation_tstats
 #' @docType data
diff --git a/R/getDegTx.R b/R/getDegTx.R
index 9a65b17..f9e4f7e 100644
--- a/R/getDegTx.R
+++ b/R/getDegTx.R
@@ -19,8 +19,9 @@
 #' These proportions were then added to our `model.matrix()` and the union of the top 1000 transcripts in the interaction model,
 #' the main effect model, and the cell proportions model were used to generate this model of qSVs.
 #'
-#' @param assayname character string specifying the name of the assay desired in rse_tx
 #' @param sig_transcripts A list of transcripts determined to have degradation signal in the qsva expanded paper.
+#' @param assayname character string specifying the name of the assay desired in rse_tx
+#' @param verbose specify if the function should report how many model transcripts were matched
 #'
 #' @return A
 #'  [RangedSummarizedExperiment-class][SummarizedExperiment::RangedSummarizedExperiment-class]
@@ -31,28 +32,38 @@
 #' @import rlang
 #'
 #' @examples
-#' getDegTx(covComb_tx_deg)
-#' stopifnot(mean(rowMeans(assays(covComb_tx_deg)$tpm)) > 1)
-getDegTx <- function(rse_tx, type = c("cell_component", "standard", "top1500"), sig_transcripts = select_transcripts(type), assayname = "tpm") {
-  
-  type = arg_match(type)
-  
+#' degTx <- getDegTx(rse_tx, "standard")
+getDegTx <- function(rse_tx, type = c("cell_component", "standard", "top1500"),
+                     sig_transcripts = NULL, assayname = "tpm", verbose = TRUE) {
+
+  #type = arg_match(type)
+  if (is.null(sig_transcripts)) {
+    type = arg_match(type)
+    sig_transcripts <- select_transcripts(type)
+  } else {
+    type = "custom"
+  }
   # Validate rse_tx is a RangedSummarizedExperiment object
   if (!is(rse_tx, "RangedSummarizedExperiment")) {
     stop("'rse_tx' must be a RangedSummarizedExperiment object.", call. = FALSE)
   }
-  
+
   # Check if assayname is in assayNames
   if (!assayname %in% assayNames(rse_tx)) {
     stop(sprintf("'%s' is not in assayNames(rse_tx).", assayname), call. = FALSE)
   }
-  
-  # Check for validity and matching of tx names
-  sig_transcripts = check_tx_names(rownames(rse_tx), sig_transcripts, 'rownames(rse_tx)', 'sig_transcripts')
-  
-  # Subset rse_tx to include sig_transcripts
-  rse_tx <- rse_tx[rownames(rse_tx) %in% sig_transcripts, , drop = FALSE]
-  
+
+  # Check for validity and matching of tx names and return the tx subset indexes in rse_tx
+  wtx <- which_tx_names(rownames(rse_tx), sig_transcripts)
+  if (length(wtx) == 0) {
+    stop("No transcripts found in the '",type, "' degradation model transcripts" )
+  }
+
+  if (verbose) {
+      message("   '",type,"' degradation model transcripts found: ", length(wtx))
+  }
+  rse_tx <- rse_tx[wtx, , drop = FALSE]
+
   # Check if the row means is greater than 1
   if (mean(rowMeans(assays(rse_tx)[[assayname]])) < 1) {
     warning("The transcripts selected are lowly expressed in your dataset. This can impact downstream analysis.")
diff --git a/R/getPCs.R b/R/getPCs.R
index 83412d9..08d66a3 100644
--- a/R/getPCs.R
+++ b/R/getPCs.R
@@ -11,7 +11,7 @@
 #' @importFrom stats prcomp
 #' @import SummarizedExperiment
 #' @examples
-#' getPCs(covComb_tx_deg, "tpm")
+#' getPCs(rse_tx, "tpm")
 getPCs <- function(rse_tx, assayname = "tpm") {
   
   # Validate rse_tx is a RangedSummarizedExperiment object
diff --git a/R/get_qsvs.R b/R/get_qsvs.R
index 22d1d62..6c54109 100644
--- a/R/get_qsvs.R
+++ b/R/get_qsvs.R
@@ -12,7 +12,7 @@
 #' @export
 #'
 #' @examples
-#' qsv <- getPCs(covComb_tx_deg, "tpm")
+#' qsv <- getPCs(rse_tx, "tpm")
 #' get_qsvs(qsv, 2)
 get_qsvs <- function(qsvPCs, k) {
   
diff --git a/R/k_qsvs.R b/R/k_qsvs.R
index 79b0e0d..3903f5b 100644
--- a/R/k_qsvs.R
+++ b/R/k_qsvs.R
@@ -14,10 +14,10 @@
 #' @import SummarizedExperiment
 #' @examples
 #' ## First we need to define a statistical model. We'll use the example
-#' ## covComb_tx_deg data. Note that the model you'll use in your own data
+#' ## rse_tx data. Note that the model you'll use in your own data
 #' ## might look different from this model.
 #' mod <- model.matrix(~ mitoRate + Region + rRNA_rate + totalAssignedGene + RIN,
-#'     data = colData(covComb_tx_deg)
+#'     data = colData(rse_tx)
 #' )
 #'
 #' ## To ensure that the results are reproducible, you will need to set a
@@ -25,7 +25,7 @@
 #' ## sva::num.sv() which needs a random seed to ensure reproducibility of the
 #' ## results.
 #' set.seed(20230621)
-#' k_qsvs(covComb_tx_deg, mod, "tpm")
+#' k_qsvs(rse_tx, mod, "tpm")
 k_qsvs <- function(rse_tx, mod, assayname) {
   
   # Validate rse_tx is a RangedSummarizedExperiment object
diff --git a/R/qSVA.R b/R/qSVA.R
index ad12fe1..a2d8027 100644
--- a/R/qSVA.R
+++ b/R/qSVA.R
@@ -3,14 +3,14 @@
 #' @param rse_tx A [RangedSummarizedExperiment-class][SummarizedExperiment::RangedSummarizedExperiment-class] object containing
 #' the transcript data desired to be studied.
 #' @param type a character string specifying which model you would
-#'  like to use when selecting a degradation matrix.
-#' @param sig_transcripts A list of transcripts that are associated with
-#' degradation signal. Use `select_transcripts()` to select sets of transcripts
-#' identified by the qSVA expanded paper. Specifying a `character()` input of
-#' ENSEMBL transcript IDs (or whatever values you have at `rownames(rse_tx)`)
-#' obtained outside of `select_transcripts()` overrides
-#' the user friendly `type` argument. That is, this argument provides more fine
-#' tuning options for advanced users.
+#'  like to use from the sets of signature transcripts identified
+#'  by the qsvaR package. This can be omitted if a custom set of
+#'  transcripts is provided to sig_transcripts.
+#' @param sig_transcripts A list of transcript IDs that are associated
+#'  with degradation signal. Specifying a `character()` input with ENSEMBL
+#' transcript IDs (whose values should match entries in `rownames(rse_tx)`).
+#' This argument provides a custom list of transcripts for adjusting
+#' for degradation; this should be used instead of the `type` argument.
 #' @param mod Model Matrix with necessary variables the you would
 #'  model for in differential expression
 #' @param assayname character string specifying the name of
@@ -21,10 +21,10 @@
 #'
 #' @examples
 #' ## First we need to define a statistical model. We'll use the example
-#' ## covComb_tx_deg data. Note that the model you'll use in your own data
+#' ## rse_tx data. Note that the model you'll use in your own data
 #' ## might look different from this model.
 #' mod <- model.matrix(~ mitoRate + Region + rRNA_rate + totalAssignedGene + RIN,
-#'     data = colData(covComb_tx_deg)
+#'     data = colData(rse_tx)
 #' )
 #'
 #' ## To ensure that the results are reproducible, you will need to set a
@@ -32,32 +32,29 @@
 #' ## sva::num.sv() which needs a random seed to ensure reproducibility of the
 #' ## results.
 #' set.seed(20230621)
-#' qSVA(rse_tx = covComb_tx_deg, type = "cell_component", mod = mod, assayname = "tpm")
+#' qSVA(rse_tx = rse_tx, type = "cell_component", mod = mod, assayname = "tpm")
 #'
 qSVA <-
-    function(rse_tx,
-    type = c("cell_component", "standard", "top1500"),
-    sig_transcripts = select_transcripts(type),
-    mod,
-    assayname) {
-        ## We don't need to pass type to getDegTx() since it's not used internally
-        ## once the sig_transcripts have been defined.
-      
-      type = arg_match(type)
-      
+    function(rse_tx,  type = c("cell_component", "standard", "top1500"),
+                      sig_transcripts = NULL,    mod,   assayname) {
+
+      if (is.null(sig_transcripts)) {
+        type = arg_match(type) # must be one of those in the list if sig_transcripts is NULL
+      }
+
       # Validate rse_tx is a RangedSummarizedExperiment object
       if (!is(rse_tx, "RangedSummarizedExperiment")) {
         stop("'rse_tx' must be a RangedSummarizedExperiment object.", call. = FALSE)
       }
-      
+
       # Check if assayname is in assayNames
       if (!assayname %in% assayNames(rse_tx)) {
         stop(sprintf("'%s' is not in assayNames(rse_tx).", assayname), call. = FALSE)
       }
-      
+
       # Get the qSVs
       DegTx <-
-            getDegTx(rse_tx, sig_transcripts = sig_transcripts, assayname = assayname)
+            getDegTx(rse_tx, type = type, sig_transcripts = sig_transcripts, assayname = assayname)
         PCs <- getPCs(DegTx, assayname)
         k <- k_qsvs(DegTx, mod = mod, assayname = assayname)
         qSV <- get_qsvs(PCs, k)
diff --git a/R/rse_tx-data.R b/R/rse_tx-data.R
new file mode 100644
index 0000000..d4ab408
--- /dev/null
+++ b/R/rse_tx-data.R
@@ -0,0 +1,13 @@
+#' Example of RSE object with RNA-seq transcript quantification data
+#'
+#' This data is a [RangedSummarizedExperiment-class][SummarizedExperiment::RangedSummarizedExperiment-class]
+#' with transcript quantification data stored in an "tpm" assay. It is
+#'  used to demonstrate the use of qsvaR in bulk RNA-seq data.
+#'
+#'
+#' @name rse_tx
+#' @docType data
+#' @format A [RangedSummarizedExperiment-class][SummarizedExperiment::RangedSummarizedExperiment-class]
+#' @keywords datasets
+#' @seealso [getPCs] [k_qsvs] [getDegTx] [qSVA]
+NULL
diff --git a/R/utils.R b/R/utils.R
index 57cc94b..f8f202d 100644
--- a/R/utils.R
+++ b/R/utils.R
@@ -1,59 +1,55 @@
-#' Check validity of transcript vectors
+
+
+#' Remove version number from Gencode/Ensembl transcript names
 #'
-#' This function is used to check if the tx1 and tx2 are GENCODE or ENSEMBL and print an error message if it's not and return a character vector of transcripts in tx2 that are in tx1.
+#' This function removes the Gencode/ENSEMBL version from the transcript ID, while protecting _PAR_Y suffixes if present
 #'
-#' @param tx1 A `character()` vector of GENCODE or ENSEMBL transcripts.
-#' @param tx2 A `character()` vector of GENCODE or ENSEMBL transcripts.
+#' @param txnames A `character()` vector of GENCODE or ENSEMBL transcript IDs
 #'
-#' @param arg_name1 A `character(1)` vector of description of tx1
-#' @param arg_name2 A `character(1)` vector of description of tx2
 #'
 #' @return A
-#'  `character()` vector of transcripts in `tx2` that are in `tx1`.
+#'  `character()` vector of transcript names without versioning
 #'
 #' @export
 #'
 #' @examples
-#' sig_transcripts = select_transcripts("cell_component")
-#' check_tx_names(rownames(covComb_tx_deg), sig_transcripts, 'rownames(covComb_tx_deg)', 'sig_transcripts')
+#' ensIDs <-  normalize_tx_names(rownames(rse_tx))
 
+normalize_tx_names <- function(txnames) {
+  sub('(ENST\\d+)\\.\\d+(.*)$','\\1\\2', txnames, perl=TRUE)
+}
 
-check_tx_names = function(tx1, tx2, arg_name1, arg_name2) {
-  #   Functions for checking whether a vector of transcripts all match GENCODE
-  #   or ENSEMBL naming conventions
-  is_gencode = function(x) all(grepl("^ENST.*?\\.", x))
-  is_ensembl = function(x) all(grepl("^ENST", x) & !grepl("\\.", x))
-  
-  #   Check that both vectors either follow GENCODE or ENSEMBL
-  if (!is_gencode(tx1) && !is_ensembl(tx1)) {
-    stop(
-      sprintf(
-        "'%s' must use either all GENCODE or all ENSEMBL transcript IDs",
-        arg_name1
-      )
-    )
-  }
-  if (!is_gencode(tx2) && !is_ensembl(tx2)) {
-    stop(
-      sprintf(
-        "'%s' must use either all GENCODE or all ENSEMBL transcript IDs",
-        arg_name2
-      )
-    )
-  }
-  
-  #   Change 'tx2' to match 'tx1', noting that the case where 'tx1' is GENCODE
-  #   but 'tx2' is ENSEMBL is not allowed (and an error will be thrown further
-  #   down)
-  if (is_gencode(tx2) && is_ensembl(tx1)) {
-    tx2 = sub('\\..*', '', tx2)
+
+#' Check validity of transcript vectors and return a vector matching indexes in tx1
+#'
+#' This function is used to check if tx1 and tx2 are GENCODE or ENSEMBL transcript IDs
+#' and return an integer vector of tx1 transcript indexes that are in tx2.
+#'
+#' @param txnames A `character()` vector of GENCODE or ENSEMBL transcript IDs.
+#' @param sig_tx A `character()` vector of GENCODE or ENSEMBL signature transcript IDs.
+#'
+#'
+#' @return A
+#'  `integer()` vector of `txnames` transcript indexes in `sig_tx`.
+#'
+#' @export
+#'
+#' @examples
+#' sig_tx <-  select_transcripts("cell_component")
+#' whichTx <- which_tx_names(rownames(rse_tx), sig_tx)
+
+which_tx_names = function(txnames, sig_tx) {
+  ## Between releases 25 and 43, PAR genes and transcripts had the "_PAR_Y" suffix appended to their identifiers.
+  ## Since release 44, these have their own IDs
+  if (!all(grepl("^ENST\\d+", txnames))) {
+    stop("The transcript names must be ENSEMBL or Gencode IDs (ENST...)" )
   }
-  
-  #   At least some transcripts must overlap between 'tx1' and 'tx2'
-  if (!any(tx2 %in% tx1)) {
-    stop(sprintf("None of '%s' are in '%s'", arg_name2, arg_name1))
+  if (!all(grepl("^ENST\\d+", sig_tx))) {
+    stop("The signature transcript names must be ENSEMBL or Gencode IDs (ENST...)" )
   }
-  
-  #   Since only 'tx2' was modified, return the changed copy
-  return(tx2)
-}
\ No newline at end of file
+  ## normalize the transcript names
+  r_tx <- normalize_tx_names(txnames)
+  s_tx <- normalize_tx_names(sig_tx)
+  which(r_tx %in% s_tx)
+}
+
diff --git a/data-raw/covComb_tx_deg.R b/data-raw/covComb_tx_deg.R
deleted file mode 100644
index f81517f..0000000
--- a/data-raw/covComb_tx_deg.R
+++ /dev/null
@@ -1,6 +0,0 @@
-## code to prepare `covComb_tx_deg` dataset goes here
-
-## change to jhpce path
-load("data/covComb_tx_deg.rda")
-
-usethis::use_data(covComb_tx_deg, overwrite = TRUE)
diff --git a/data-raw/rse_tx.R b/data-raw/rse_tx.R
new file mode 100644
index 0000000..fb58494
--- /dev/null
+++ b/data-raw/rse_tx.R
@@ -0,0 +1,5 @@
+## code to prepare `rse_tx` example goes here
+
+load("data/rse_tx.rda")
+# the above loads rse_tx
+usethis::use_data(rse_tx, overwrite = TRUE)
diff --git a/data/covComb_tx_deg.rda b/data/covComb_tx_deg.rda
deleted file mode 100644
index 08e72ca..0000000
Binary files a/data/covComb_tx_deg.rda and /dev/null differ
diff --git a/data/rse_tx.rda b/data/rse_tx.rda
new file mode 100644
index 0000000..cc3ff6d
Binary files /dev/null and b/data/rse_tx.rda differ
diff --git a/man/DEqual.Rd b/man/DEqual.Rd
index c4b3b3e..a47fbd1 100644
--- a/man/DEqual.Rd
+++ b/man/DEqual.Rd
@@ -4,12 +4,37 @@
 \alias{DEqual}
 \title{Differential expression quality (DEqual) plot}
 \usage{
-DEqual(DE)
+DEqual(
+  DE,
+  deg_tstats = qsvaR::degradation_tstats,
+  show.legend = TRUE,
+  show.cor = c("caption", "corner-top", "corner-bottom", "none"),
+  font.size = 12,
+  cor.size = font.size/2,
+  cor.label = "cor: "
+)
 }
 \arguments{
-\item{DE}{a \code{data.frame()} with one column containing the t-statistics from
-Differential Expression, typically generated with \code{limma::topTable()}.
-The \code{rownames(DE)} should be transcript GENCODE IDs.}
+\item{DE}{a \code{data.frame()} with a column "t" containing the t-statistics
+from Differential Expression, typically generated with \code{limma::topTable()}.
+\code{rownames(DE)} must have transcript Ensembl/Gencode IDs.}
+
+\item{deg_tstats}{an optional\code{data.frame()} with a column "t" containing
+t-statistics resulted from a degradation experiment. Default is the
+internal \code{qsvaR::degradation_tstats} from the package authors.}
+
+\item{show.legend}{logical (default TRUE) to show legend in the plot}
+
+\item{show.cor}{specify where to show the correlation value. Can be one of
+"caption", "corner-top", "corner-bottom", or "none".}
+
+\item{font.size}{numeric value to set the base font size of the plot}
+
+\item{cor.size}{numeric (default font.size/2) to set the font size for the
+correlation text}
+
+\item{cor.label}{character (default "cor: ") to set the text preceding the
+correlation value}
 }
 \value{
 a \code{ggplot} object of the DE t-statistic vs
@@ -24,7 +49,7 @@ included in Collado-Torres et al, Neuron, 2019
 \url{https://doi.org/10.1016/j.neuron.2019.05.013}. This function compares your
 t-statistics of interest computed on transcripts against the
 t-statistics from degradation time adjusting for the six brain regions from
-degradation experiment data used for determining \code{covComb_tx_deg}.
+degradation experiment data used for determining \code{rse_tx}.
 }
 \examples{
 
diff --git a/man/check_tx_names.Rd b/man/check_tx_names.Rd
deleted file mode 100644
index bc3c515..0000000
--- a/man/check_tx_names.Rd
+++ /dev/null
@@ -1,28 +0,0 @@
-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/utils.R
-\name{check_tx_names}
-\alias{check_tx_names}
-\title{Check validity of transcript vectors}
-\usage{
-check_tx_names(tx1, tx2, arg_name1, arg_name2)
-}
-\arguments{
-\item{tx1}{A \code{character()} vector of GENCODE or ENSEMBL transcripts.}
-
-\item{tx2}{A \code{character()} vector of GENCODE or ENSEMBL transcripts.}
-
-\item{arg_name1}{A \code{character(1)} vector of description of tx1}
-
-\item{arg_name2}{A \code{character(1)} vector of description of tx2}
-}
-\value{
-A
-\code{character()} vector of transcripts in \code{tx2} that are in \code{tx1}.
-}
-\description{
-This function is used to check if the tx1 and tx2 are GENCODE or ENSEMBL and print an error message if it's not and return a character vector of transcripts in tx2 that are in tx1.
-}
-\examples{
-sig_transcripts = select_transcripts("cell_component")
-check_tx_names(rownames(covComb_tx_deg), sig_transcripts, 'rownames(covComb_tx_deg)', 'sig_transcripts')
-}
diff --git a/man/covComb_tx_deg.Rd b/man/covComb_tx_deg.Rd
deleted file mode 100644
index 623f143..0000000
--- a/man/covComb_tx_deg.Rd
+++ /dev/null
@@ -1,19 +0,0 @@
-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/covComb_tx_deg-data.R
-\docType{data}
-\name{covComb_tx_deg}
-\alias{covComb_tx_deg}
-\title{RSE object of RNA-seq data that serves as output for degradation analysis}
-\format{
-A \link[SummarizedExperiment:RangedSummarizedExperiment-class]{RangedSummarizedExperiment-class}
-}
-\description{
-This data was generated from an experiment using degraded RNA-seq samples
-post-mortem brain tissue. The transcripts included are the result of the qsva
-expanded framework study and will be used to remove the effect of degradation
-in bulk RNA-seq data.
-}
-\seealso{
-\link{getPCs} \link{k_qsvs} \link{getDegTx}
-}
-\keyword{datasets}
diff --git a/man/degradation_tstats.Rd b/man/degradation_tstats.Rd
index 31e1413..545c578 100644
--- a/man/degradation_tstats.Rd
+++ b/man/degradation_tstats.Rd
@@ -9,11 +9,11 @@ A \code{data.frame()} with the \code{t} statistics for degradation time. The
 \code{rownames()} are the GENCODE transcript IDs.
 }
 \description{
-These t-statistics are derived from the same data that was used for
-\link{covComb_tx_deg}. They are the results from main model where we determined
-the relationship with degradation time adjusting for the brain region (so
-parallel degradation effects across brain regions). They are used for
-plotting in \code{DEqual()}.
+These t-statistics are derived from the degradation timepoints data
+built into qsvaR. They are the results from multiple models where
+we determined the association of transcripts with degradation time
+adjusting for brain region (so parallel degradation effects across
+brain regions). They are used for plotting in \code{DEqual()}.
 }
 \seealso{
 \link{DEqual}
diff --git a/man/getDegTx.Rd b/man/getDegTx.Rd
index 2765b17..baefbbb 100644
--- a/man/getDegTx.Rd
+++ b/man/getDegTx.Rd
@@ -7,8 +7,9 @@
 getDegTx(
   rse_tx,
   type = c("cell_component", "standard", "top1500"),
-  sig_transcripts = select_transcripts(type),
-  assayname = "tpm"
+  sig_transcripts = NULL,
+  assayname = "tpm",
+  verbose = TRUE
 )
 }
 \arguments{
@@ -30,6 +31,8 @@ the main effect model, and the cell proportions model were used to generate this
 \item{sig_transcripts}{A list of transcripts determined to have degradation signal in the qsva expanded paper.}
 
 \item{assayname}{character string specifying the name of the assay desired in rse_tx}
+
+\item{verbose}{specify if the function should report how many model transcripts were matched}
 }
 \value{
 A
@@ -43,6 +46,5 @@ postmortem brain tissues. This object can later be used to obtain the principle
 necessary to remove the effect of degradation in differential expression.
 }
 \examples{
-getDegTx(covComb_tx_deg)
-stopifnot(mean(rowMeans(assays(covComb_tx_deg)$tpm)) > 1)
+degTx <- getDegTx(rse_tx, "standard")
 }
diff --git a/man/getPCs.Rd b/man/getPCs.Rd
index 83f3ae7..9a50d78 100644
--- a/man/getPCs.Rd
+++ b/man/getPCs.Rd
@@ -18,5 +18,5 @@ prcomp object generated by taking the pcs of degraded transcripts
 This function returns the pcs from the obtained RangedSummarizedExperiment object of selected transcripts
 }
 \examples{
-getPCs(covComb_tx_deg, "tpm")
+getPCs(rse_tx, "tpm")
 }
diff --git a/man/get_qsvs.Rd b/man/get_qsvs.Rd
index 2a01244..68a51d2 100644
--- a/man/get_qsvs.Rd
+++ b/man/get_qsvs.Rd
@@ -20,6 +20,6 @@ Using the pcs and the k number of components be included,
 we generate the qsva matrix.
 }
 \examples{
-qsv <- getPCs(covComb_tx_deg, "tpm")
+qsv <- getPCs(rse_tx, "tpm")
 get_qsvs(qsv, 2)
 }
diff --git a/man/k_qsvs.Rd b/man/k_qsvs.Rd
index 0fd9b6a..90cb1a4 100644
--- a/man/k_qsvs.Rd
+++ b/man/k_qsvs.Rd
@@ -23,10 +23,10 @@ Apply num.sv algorithm to determine the number of pcs to be included
 }
 \examples{
 ## First we need to define a statistical model. We'll use the example
-## covComb_tx_deg data. Note that the model you'll use in your own data
+## rse_tx data. Note that the model you'll use in your own data
 ## might look different from this model.
 mod <- model.matrix(~ mitoRate + Region + rRNA_rate + totalAssignedGene + RIN,
-    data = colData(covComb_tx_deg)
+    data = colData(rse_tx)
 )
 
 ## To ensure that the results are reproducible, you will need to set a
@@ -34,5 +34,5 @@ mod <- model.matrix(~ mitoRate + Region + rRNA_rate + totalAssignedGene + RIN,
 ## sva::num.sv() which needs a random seed to ensure reproducibility of the
 ## results.
 set.seed(20230621)
-k_qsvs(covComb_tx_deg, mod, "tpm")
+k_qsvs(rse_tx, mod, "tpm")
 }
diff --git a/man/normalize_tx_names.Rd b/man/normalize_tx_names.Rd
new file mode 100644
index 0000000..5e4174b
--- /dev/null
+++ b/man/normalize_tx_names.Rd
@@ -0,0 +1,21 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/utils.R
+\name{normalize_tx_names}
+\alias{normalize_tx_names}
+\title{Remove version number from Gencode/Ensembl transcript names}
+\usage{
+normalize_tx_names(txnames)
+}
+\arguments{
+\item{txnames}{A \code{character()} vector of GENCODE or ENSEMBL transcript IDs}
+}
+\value{
+A
+\code{character()} vector of transcript names without versioning
+}
+\description{
+This function removes the Gencode/ENSEMBL version from the transcript ID, while protecting _PAR_Y suffixes if present
+}
+\examples{
+ensIDs <-  normalize_tx_names(rownames(rse_tx))
+}
diff --git a/man/qSVA.Rd b/man/qSVA.Rd
index 48b5fb5..30bae9b 100644
--- a/man/qSVA.Rd
+++ b/man/qSVA.Rd
@@ -7,7 +7,7 @@
 qSVA(
   rse_tx,
   type = c("cell_component", "standard", "top1500"),
-  sig_transcripts = select_transcripts(type),
+  sig_transcripts = NULL,
   mod,
   assayname
 )
@@ -17,15 +17,15 @@ qSVA(
 the transcript data desired to be studied.}
 
 \item{type}{a character string specifying which model you would
-like to use when selecting a degradation matrix.}
+like to use from the sets of signature transcripts identified
+by the qsvaR package. This can be omitted if a custom set of
+transcripts is provided to sig_transcripts.}
 
-\item{sig_transcripts}{A list of transcripts that are associated with
-degradation signal. Use \code{select_transcripts()} to select sets of transcripts
-identified by the qSVA expanded paper. Specifying a \code{character()} input of
-ENSEMBL transcript IDs (or whatever values you have at \code{rownames(rse_tx)})
-obtained outside of \code{select_transcripts()} overrides
-the user friendly \code{type} argument. That is, this argument provides more fine
-tuning options for advanced users.}
+\item{sig_transcripts}{A list of transcript IDs that are associated
+with degradation signal. Specifying a \code{character()} input with ENSEMBL
+transcript IDs (whose values should match entries in \code{rownames(rse_tx)}).
+This argument provides a custom list of transcripts for adjusting
+for degradation; this should be used instead of the \code{type} argument.}
 
 \item{mod}{Model Matrix with necessary variables the you would
 model for in differential expression}
@@ -41,10 +41,10 @@ A wrapper function used to perform qSVA in one step.
 }
 \examples{
 ## First we need to define a statistical model. We'll use the example
-## covComb_tx_deg data. Note that the model you'll use in your own data
+## rse_tx data. Note that the model you'll use in your own data
 ## might look different from this model.
 mod <- model.matrix(~ mitoRate + Region + rRNA_rate + totalAssignedGene + RIN,
-    data = colData(covComb_tx_deg)
+    data = colData(rse_tx)
 )
 
 ## To ensure that the results are reproducible, you will need to set a
@@ -52,6 +52,6 @@ mod <- model.matrix(~ mitoRate + Region + rRNA_rate + totalAssignedGene + RIN,
 ## sva::num.sv() which needs a random seed to ensure reproducibility of the
 ## results.
 set.seed(20230621)
-qSVA(rse_tx = covComb_tx_deg, type = "cell_component", mod = mod, assayname = "tpm")
+qSVA(rse_tx = rse_tx, type = "cell_component", mod = mod, assayname = "tpm")
 
 }
diff --git a/man/rse_tx.Rd b/man/rse_tx.Rd
new file mode 100644
index 0000000..4edc43e
--- /dev/null
+++ b/man/rse_tx.Rd
@@ -0,0 +1,18 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/rse_tx-data.R
+\docType{data}
+\name{rse_tx}
+\alias{rse_tx}
+\title{Example of RSE object with RNA-seq transcript quantification data}
+\format{
+A \link[SummarizedExperiment:RangedSummarizedExperiment-class]{RangedSummarizedExperiment-class}
+}
+\description{
+This data is a \link[SummarizedExperiment:RangedSummarizedExperiment-class]{RangedSummarizedExperiment-class}
+with transcript quantification data stored in an "tpm" assay. It is
+used to demonstrate the use of qsvaR in bulk RNA-seq data.
+}
+\seealso{
+\link{getPCs} \link{k_qsvs} \link{getDegTx} \link{qSVA}
+}
+\keyword{datasets}
diff --git a/man/which_tx_names.Rd b/man/which_tx_names.Rd
new file mode 100644
index 0000000..e0f7f37
--- /dev/null
+++ b/man/which_tx_names.Rd
@@ -0,0 +1,25 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/utils.R
+\name{which_tx_names}
+\alias{which_tx_names}
+\title{Check validity of transcript vectors and return a vector matching indexes in tx1}
+\usage{
+which_tx_names(txnames, sig_tx)
+}
+\arguments{
+\item{txnames}{A \code{character()} vector of GENCODE or ENSEMBL transcript IDs.}
+
+\item{sig_tx}{A \code{character()} vector of GENCODE or ENSEMBL signature transcript IDs.}
+}
+\value{
+A
+\code{integer()} vector of \code{txnames} transcript indexes in \code{sig_tx}.
+}
+\description{
+This function is used to check if tx1 and tx2 are GENCODE or ENSEMBL transcript IDs
+and return an integer vector of tx1 transcript indexes that are in tx2.
+}
+\examples{
+sig_tx <-  select_transcripts("cell_component")
+whichTx <- which_tx_names(rownames(rse_tx), sig_tx)
+}
diff --git a/tests/testthat/test-DEqual.R b/tests/testthat/test-DEqual.R
index 3cb4f04..9e2ea56 100644
--- a/tests/testthat/test-DEqual.R
+++ b/tests/testthat/test-DEqual.R
@@ -12,7 +12,7 @@ random_de <- data.frame(
 # Test if DEqual throws an error when input is not a dataframe
 test_that("DEqual throws an error for non-dataframe input", {
   # Test if DEqual throws an error when input is not a dataframe
-  expect_error(DEqual(covComb_tx_deg), "The input to DEqual is not a dataframe.")
+  expect_error(DEqual(rse_tx), "The input to DEqual is not a dataframe.")
 })
 
 # Test when 't' is not in the columns
diff --git a/tests/testthat/test-getDegTx.R b/tests/testthat/test-getDegTx.R
index 4f2bc7a..fbb8f5e 100644
--- a/tests/testthat/test-getDegTx.R
+++ b/tests/testthat/test-getDegTx.R
@@ -1,49 +1,42 @@
 # Filter out lowly expressed transcripts and test if the number of rows in getDegTx output matches expected transcript count
-rse_tx_low <- covComb_tx_deg[rowMeans(assays(covComb_tx_deg)$tpm) < 1, ]
+rse_tx_low <- rse_tx[rowMeans(assays(rse_tx)$tpm) < 1, ]
 test_that("length for number of rows is the same a length sig_transcripts", {
-    expect_equal(length(rownames(getDegTx(covComb_tx_deg))), length(select_transcripts("cell_component")))
+    expect_equal(length(rownames(getDegTx(rse_tx))), length(select_transcripts("cell_component")))
 })
 
 # Test if number of columns in getDegTx output matches number of columns in original dataset
 test_that("length for number of columns is the same a length sig_transcripts", {
-    expect_equal(length(colnames(getDegTx(covComb_tx_deg))), length(colnames(covComb_tx_deg)))
+    expect_equal(length(colnames(getDegTx(rse_tx))), length(colnames(rse_tx)))
 })
 
 # Test if getDegTx returns an object of the same class as its input
 test_that("output is an RSE", {
-    expect_equal(class(getDegTx(covComb_tx_deg)), class(covComb_tx_deg))
+    expect_equal(class(getDegTx(rse_tx)), class(rse_tx))
 })
 
 # Test for a warning when getDegTx is used on a dataset with lowly expressed transcripts
 test_that("test warning output for lowly expressed transcripts", {
-    expect_warning(getDegTx(rse_tx_low), "The transcripts selected are lowly expressed in your dataset. This can impact downstream analysis.")
+    expect_warning(getDegTx(rse_tx_low, verbose=FALSE),
+            "The transcripts selected are lowly expressed in your dataset. This can impact downstream analysis.")
 })
 
 # Test for rownames starting with "ENST"
-test_that("getDegTx correctly processes covComb_tx_deg", {
-  # If covComb_tx_deg is correctly structured and all rownames start with "ENST", expect no error
-  expect_silent(getDegTx(covComb_tx_deg))
+test_that("getDegTx correctly processes rse_tx", {
+  # If rse_tx is correctly structured and all rownames start with "ENST", expect no error
+  expect_silent(getDegTx(rse_tx, verbose=FALSE))
 })
 
-# Test where at least one sig_transcript is in covComb_tx_deg rownames
-test_that("At least one sig_transcript is in covComb_tx_deg rownames", {
-  sig_transcripts <- select_transcripts("cell_component")
-  expect_silent({
-    # Check if any of the sig_transcripts are in covComb_tx_deg rownames
-    getDegTx(covComb_tx_deg, sig_transcripts = sig_transcripts)
-  })
-})
 
 # Test whether getDegTx gives the same results with original and altered row names
 test_that("getDegTx works with original and altered row names", {
   set.seed(123)
-  # Apply getDegTx to covComb_tx_deg
-  original_results <- getDegTx(covComb_tx_deg,sig_transcripts =select_transcripts("cell_component"))
-  
-  # Alter the row names of covComb_tx_deg and apply getDegTx
-  altered_covComb_tx_deg <- covComb_tx_deg
-  rownames(altered_covComb_tx_deg) <- gsub("\\..*", "", rownames(covComb_tx_deg))
-  altered_results <- getDegTx(altered_covComb_tx_deg,sig_transcripts =select_transcripts("cell_component"))
+  # Apply getDegTx to rse_tx
+  original_results <- getDegTx(rse_tx, sig_transcripts =select_transcripts("cell_component"))
+
+  # Alter the row names of rse_tx and apply getDegTx
+  altered_rse_tx <- rse_tx
+  rownames(altered_rse_tx) <- gsub("\\..\\d+", "", rownames(rse_tx))
+  altered_results <- getDegTx(altered_rse_tx, sig_transcripts =select_transcripts("cell_component"))
   rownames(altered_results) <- rownames(original_results)
   # Test if two objects identical
   expect_identical(original_results, altered_results)
@@ -51,7 +44,7 @@ test_that("getDegTx works with original and altered row names", {
 
 # Test for assayname not in assayNames
 test_that("getDegTx throws an error when assayname is not in assayNames", {
-  expect_error(getDegTx(covComb_tx_deg, assayname = "not_in_assayNames"), "'not_in_assayNames' is not in assayNames\\(rse_tx\\).")
+  expect_error(getDegTx(rse_tx, assayname = "not_in_assayNames"), "'not_in_assayNames' is not in assayNames\\(rse_tx\\).")
 })
 
 # Test for input is an rse object
diff --git a/tests/testthat/test-getPCs.R b/tests/testthat/test-getPCs.R
index 13d359a..35e75e8 100644
--- a/tests/testthat/test-getPCs.R
+++ b/tests/testthat/test-getPCs.R
@@ -1,10 +1,10 @@
 test_that("output is a prcomp", {
-    expect_equal(class(getPCs(covComb_tx_deg, "tpm")), "prcomp")
+    expect_equal(class(getPCs(rse_tx, "tpm")), "prcomp")
 })
 
 # Test for assayname not in assayNames
 test_that("getPCs throws an error when assayname is not in assayNames", {
-  expect_error(getPCs(covComb_tx_deg, assayname = "not_in_assayNames"), "'not_in_assayNames' is not in assayNames\\(rse_tx\\).")
+  expect_error(getPCs(rse_tx, assayname = "not_in_assayNames"), "'not_in_assayNames' is not in assayNames\\(rse_tx\\).")
 })
 
 # Test for input is an rse object
diff --git a/tests/testthat/test-get_qsvs.R b/tests/testthat/test-get_qsvs.R
index d668299..4667ce4 100644
--- a/tests/testthat/test-get_qsvs.R
+++ b/tests/testthat/test-get_qsvs.R
@@ -1,13 +1,13 @@
-mod <- model.matrix(~ mitoRate + Region + rRNA_rate + totalAssignedGene + RIN, data = colData(covComb_tx_deg))
-k <- k_qsvs(covComb_tx_deg, mod, "tpm")
-qsv <- getPCs(covComb_tx_deg, "tpm")
+mod <- model.matrix(~ mitoRate + Region + rRNA_rate + totalAssignedGene + RIN, data = colData(rse_tx))
+k <- k_qsvs(rse_tx, mod, "tpm")
+qsv <- getPCs(rse_tx, "tpm")
 
 test_that("number of qsvs is k", {
     expect_equal(length(colnames(get_qsvs(qsv, k))), k)
 })
 
 test_that("length of qsv rownames is the same as number of samples", {
-    expect_equal(length(rownames(get_qsvs(qsv, k))), length(colnames(covComb_tx_deg)))
+    expect_equal(length(rownames(get_qsvs(qsv, k))), length(colnames(rse_tx)))
 })
 
 test_that("output is a matrix", {
@@ -28,5 +28,5 @@ test_that("k is higher than the number of columns throws an error", {
 })
 
 test_that("input has to be a prcomp", {
-  expect_error(get_qsvs(covComb_tx_deg, 3), "'qsvPCs' must be a prcomp object.")
+  expect_error(get_qsvs(rse_tx, 3), "'qsvPCs' must be a prcomp object.")
 })
\ No newline at end of file
diff --git a/tests/testthat/test-k_qsvs.R b/tests/testthat/test-k_qsvs.R
index e092a38..3d525ab 100644
--- a/tests/testthat/test-k_qsvs.R
+++ b/tests/testthat/test-k_qsvs.R
@@ -1,7 +1,7 @@
-mod <- model.matrix(~ mitoRate + Region + rRNA_rate + totalAssignedGene + RIN, data = colData(covComb_tx_deg))
+mod <- model.matrix(~ mitoRate + Region + rRNA_rate + totalAssignedGene + RIN, data = colData(rse_tx))
 
 # rse_tx_low has low expression
-rse_tx_low <- covComb_tx_deg[rowMeans(assays(covComb_tx_deg)$tpm) < 1, ]
+rse_tx_low <- rse_tx[rowMeans(assays(rse_tx)$tpm) < 1, ]
 
 # mod2 is not full rank
 mod2 <- mod
@@ -10,7 +10,7 @@ colnames(mod2)[8] <- "mitotest"
 
 ## Set a random seed
 set.seed(20230621)
-k_res <- k_qsvs(covComb_tx_deg, mod, "tpm")
+k_res <- k_qsvs(rse_tx, mod, "tpm")
 
 test_that("length pf output is 1", {
     expect_equal(length(k_res), 1)
@@ -32,30 +32,30 @@ test_that("getDegTx throws an error when input is not a RangedSummarizedExperime
 
 # Test for assayname not in assayNames
 test_that("k_qsvs throws an error when assayname is not in assayNames", {
-  expect_error(k_qsvs(covComb_tx_deg, assayname = "not_in_assayNames"), "'not_in_assayNames' is not in assayNames\\(rse_tx\\).")
+  expect_error(k_qsvs(rse_tx, assayname = "not_in_assayNames"), "'not_in_assayNames' is not in assayNames\\(rse_tx\\).")
 })
 
 # Test when number of rows in 'mod' does not match number of columns in 'rse_tx'
 test_that("Number of rows in 'mod' does not match number of columns in 'rse_tx'", {
   mod_not_matching <- mod
   mod_not_matching <- mod_not_matching[-1, ]
-  expect_error(k_qsvs(covComb_tx_deg, mod_not_matching, "tpm"), "The number of rows in 'mod' does not match the number of input 'rse_tx' columns.")
+  expect_error(k_qsvs(rse_tx, mod_not_matching, "tpm"), "The number of rows in 'mod' does not match the number of input 'rse_tx' columns.")
 })
 
 test_that("non-full rank data throws error", {
     set.seed(20230621)
-    expect_error(qSVA(rse_tx = covComb_tx_deg, type = "cell_component", mod = mod2, assayname = "tpm"), "matrix is not full rank")
+    expect_error(qSVA(rse_tx = rse_tx, type = "cell_component", mod = mod2, assayname = "tpm"), "matrix is not full rank")
 })
 
 
 test_that("test that full rank matrix works correctly", {
     set.seed(20230621)
     # expect_warning(k_qsvs(rse_tx_low, mod, "tpm"), "Likely due to transcripts being not expressed in most samples")
-    expect_silent(k_qsvs(covComb_tx_deg, mod, "tpm"))
+    expect_silent(k_qsvs(rse_tx, mod, "tpm"))
 })
 
 test_that("test that mod is a matrix", {
     set.seed(20230621)
-    expect_error(k_qsvs(covComb_tx_deg, mod = "mod", assayname = "tpm"), "'mod' must be a matrix.")
+    expect_error(k_qsvs(rse_tx, mod = "mod", assayname = "tpm"), "'mod' must be a matrix.")
 })
 
diff --git a/tests/testthat/test-qSVA.R b/tests/testthat/test-qSVA.R
index 5a77ec8..31f549d 100644
--- a/tests/testthat/test-qSVA.R
+++ b/tests/testthat/test-qSVA.R
@@ -1,10 +1,10 @@
-mod <- model.matrix(~ mitoRate + Region + rRNA_rate + totalAssignedGene + RIN, data = colData(covComb_tx_deg))
+mod <- model.matrix(~ mitoRate + Region + rRNA_rate + totalAssignedGene + RIN, data = colData(rse_tx))
 
 ## Run qSVA with 2 types
 set.seed(20230621)
-qsva_cc <- qSVA(rse_tx = covComb_tx_deg, type = "cell_component", mod = mod, assayname = "tpm")
+qsva_cc <- qSVA(rse_tx = rse_tx, type = "cell_component", mod = mod, assayname = "tpm")
 set.seed(20230621)
-qsva_standard <- qSVA(rse_tx = covComb_tx_deg, type = "standard", mod = mod, assayname = "tpm")
+qsva_standard <- qSVA(rse_tx = rse_tx, type = "standard", mod = mod, assayname = "tpm")
 
 test_that("number of qsvs is k", {
     expect_equal(length(colnames(qsva_cc)), 10)
@@ -12,7 +12,7 @@ test_that("number of qsvs is k", {
 })
 
 test_that("length of qsv rownames is the same as number of samples", {
-    expect_equal(length(rownames(qsva_cc)), length(colnames(covComb_tx_deg)))
+    expect_equal(length(rownames(qsva_cc)), length(colnames(rse_tx)))
 })
 
 test_that("output is a matrix", {
@@ -25,7 +25,7 @@ test_that("output is an array", {
 
 # Test for assayname not in assayNames
 test_that("qSVA throws an error when assayname is not in assayNames", {
-  expect_error(qSVA(covComb_tx_deg, type = "standard", mod = mod,assayname = "not_in_assayNames"), "'not_in_assayNames' is not in assayNames\\(rse_tx\\).")
+  expect_error(qSVA(rse_tx, type = "standard", mod = mod,assayname = "not_in_assayNames"), "'not_in_assayNames' is not in assayNames\\(rse_tx\\).")
 })
 
 # Test for input is an rse object
diff --git a/tests/testthat/test-utils.R b/tests/testthat/test-utils.R
index 83cdeb7..2089436 100644
--- a/tests/testthat/test-utils.R
+++ b/tests/testthat/test-utils.R
@@ -1,26 +1,12 @@
 # ENSEMBL names that are not GENCODE or ENSEMBL
 
-# Test for check_tx_names transcripts throw errors if annotation is not GENCODE or ENSEMBL
+# Test for which_tx_names transcripts throw errors if annotation is not GENCODE or ENSEMBL
 test_that("check_tx_names throw error if annotation is not GENCODE or ENSEMBL", {
-  # For testing the error condition, altered manually rownames of covComb_tx_deg
-  altered_covComb_tx_deg <- covComb_tx_deg
-  rownames(altered_covComb_tx_deg) <- paste0("gene", 1:length(rownames(altered_covComb_tx_deg))) 
+  # For testing the error condition, altered manually rownames of rse_tx
+  altered_rse_tx <- rse_tx
+  rownames(altered_rse_tx) <- paste0("gene", 1:length(rownames(altered_rse_tx)))
   sig_transcripts <- select_transcripts("cell_component")
-  expect_error(check_tx_names(rownames(altered_covComb_tx_deg), sig_transcripts, 'rownames(rse_tx)', 'sig_transcripts'), "rownames\\(rse_tx\\)' must use either all GENCODE or all ENSEMBL transcript IDs")
-  expect_error(check_tx_names(sig_transcripts, rownames(altered_covComb_tx_deg), 'sig_transcripts', 'rownames(rse_tx)'), "rownames\\(rse_tx\\)' must use either all GENCODE or all ENSEMBL transcript IDs")
-})
-
-# Test for check_tx_names transcripts throw errors if annotation is not mixed GENCODE and ENSEMBL
-test_that("Mixed row names annotations throw an error", {
-  # For testing the error condition, altered manually rownames of covComb_tx_deg
-  altered_covComb_tx_deg <- covComb_tx_deg
-  rownames(altered_covComb_tx_deg)[1] <- "ENST00000442987" # Change the first rowname 
-  rownames(altered_covComb_tx_deg)[2] <- "ENST00000623083" # Change the second rowname 
-  sig_transcripts <- select_transcripts("cell_component")
-  expect_error({
-    # Check if mixed row names annotations (ENST and ENST.*?\.) throw an error
-    check_tx_names(rownames(altered_covComb_tx_deg), sig_transcripts, 'rownames(rse_tx)', 'sig_transcripts')
-    
-  }, "rownames\\(rse_tx\\)' must use either all GENCODE or all ENSEMBL transcript IDs")
+  expect_error(which_tx_names(rownames(altered_rse_tx), sig_transcripts))
+  expect_error(which_tx_names(sig_transcripts, rownames(altered_rse_tx)))
 })
 
diff --git a/vignettes/Intro_qsvaR.Rmd b/vignettes/Intro_qsvaR.Rmd
index a2fdc65..e5da174 100644
--- a/vignettes/Intro_qsvaR.Rmd
+++ b/vignettes/Intro_qsvaR.Rmd
@@ -144,6 +144,9 @@ rse_file <- BiocFileCache::bfcrpath(
     x = bfc
 )
 load(rse_file, verbose = TRUE)
+## keep only adult samples and apply minimum expression cutoff
+rse_tx <- rse_tx[, rse_tx$Age > 17 ]
+rse_tx <- rse_tx[rowMeans(assays(rse_tx)$tpm) > 0.3, ]
 ```
 
 ## Get Degradation Matrix
@@ -219,11 +222,8 @@ dim(qsvs_wrapper)
 Next we can use a standard limma package approach to do differential expression on the data. The key here is that we add our qsvs to the `model.matrix()`. Here we input our `RangedSummarizedExperiment` object and our `model.matrix()` with qSVs. Note here that the `RangedSummarizedExperiment` object is the original object loaded with the full list of transcripts, not the the one we subsetted for qSVs. This is because while PCs can be generated from a subset of genes, differential expression is best done on the full dataset. The expected output is a `sigTx` object that shows the results of differential expression.
 
 ```{r "perform DE"}
-### should be done by cbinding mod to pcs
-## subset to an expression cutoff
-rse_tx <- rse_tx[rowData(rse_tx)$passExprsCut, ]
 
-# create a model.matrix with demographic infor and qsvs
+# create a model.matrix with demographic info and qsvs
 mod_qSVA <- cbind(mod, qsvs)
 
 # log tranform transcript expression