diff --git a/DESCRIPTION b/DESCRIPTION
index aec8dd7..49e516f 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,7 +1,7 @@
 Package: scLANE
 Type: Package
 Title: Model gene expression dynamics with spline-based NB GLMs, GEEs, & GLMMs
-Version: 0.7.5
+Version: 0.7.6
 Authors@R: c(person(given = "Jack", family = "Leary", email = "j.leary@ufl.edu", role = c("aut", "cre"), comment = c(ORCID = "0009-0004-8821-3269")), 
              person(given = "Rhonda", family = "Bacher", email = "rbacher@ufl.edu", role = c("ctb", "fnd"), comment = c(ORCID = "0000-0001-5787-476X")))
 Description: This package uses truncated power basis spline models to build flexible, interpretable models of single cell gene expression over pseudotime or latent time. 
@@ -9,7 +9,7 @@ Description: This package uses truncated power basis spline models to build flex
              Downstream analysis functionalities include model comparison, dynamic gene clustering, smoothed counts generation, gene set enrichment testing, & visualization. 
 License: MIT + file LICENSE
 Encoding: UTF-8
-LazyData: false
+LazyData: true
 RoxygenNote: 7.2.1
 Depends: 
   glm2, 
diff --git a/NAMESPACE b/NAMESPACE
index 894e167..63d2bc8 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -30,6 +30,7 @@ importFrom(MASS,glm.nb)
 importFrom(MASS,negative.binomial)
 importFrom(MASS,theta.mm)
 importFrom(Matrix,colSums)
+importFrom(Matrix,t)
 importFrom(Rcpp,sourceCpp)
 importFrom(bigstatsr,as_FBM)
 importFrom(broom.mixed,tidy)
diff --git a/NEWS.md b/NEWS.md
index 8bc93eb..afdf733 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,3 +1,8 @@
+# `scLANE` v0.7.6
+
+* Added Zenodo tracking.
+* Added simulated dataset to `data/`
+
 # `scLANE` v0.7.5
 
 * Preparing for BioConductor submission i.e., reformatting code, adding documentation, etc.
diff --git a/R/data.R b/R/data.R
new file mode 100644
index 0000000..5ef1677
--- /dev/null
+++ b/R/data.R
@@ -0,0 +1,19 @@
+#' A \code{\link[SingleCellExperiment]{SingleCellExperiment}} object containing simulated counts.
+#'
+#' Data simulated using the \code{scaffold} R package for 50 dynamic and 50 static genes across 1200 cells from 3 subjects.
+#'
+#' @format An object of class \code{\link[SingleCellExperiment]{SingleCellExperiment}}.
+#' @source https://www.rhondabacher.com/scaffold-vignette.pdf
+#' @usage data(sim_counts)
+"sim_counts"
+
+#' A data.frame containing ground-truth pseudotime.
+#'
+#' The true ordering of the 1200 cells contained in \code{sim_counts}.
+#'
+#' @format An object of class \code{data.frame} with 1200 rows and one variable:
+#' \itemize{
+#'  \item PT: the true pseudotime (0.0025--1)
+#' }
+#' @usage data(sim_pseudotime)
+"sim_pseudotime"
diff --git a/R/testDynamic.R b/R/testDynamic.R
index 7256815..1a1b8cc 100644
--- a/R/testDynamic.R
+++ b/R/testDynamic.R
@@ -5,6 +5,7 @@
 #' @description This function tests whether a NB \code{marge} model is better than a null (intercept-only) NB GLM using the Likelihood Ratio Test. In effect, the test tells us whether a gene's expression changes (in any way) over pseudotime.
 #' @import glm2
 #' @import magrittr
+#' @importFrom Matrix t
 #' @importFrom bigstatsr as_FBM
 #' @importFrom foreach foreach %dopar% registerDoSEQ
 #' @importFrom doParallel registerDoParallel
@@ -45,34 +46,29 @@
 #' @seealso \code{\link[glmmTMB]{glmmTMB}}
 #' @export
 #' @examples
-#' \dontrun{
-#' testDynamic(expr.mat = raw_counts,
-#'             pt = pseudotime_df,
-#'             parallel.exec = TRUE)
-#' testDynamic(expr.mat = sce_obj,
-#'             pt = slingshot_obj,
-#'             size.factor.offset = sizeFactors(sce_obj),
-#'             genes = rownames(sce_obj)[1:100])
-#' testDynamic(expr.mat = raw_counts,
-#'             pt = pseudotime_df,
-#'             parallel.exec = TRUE,
-#'             n.cores = 8,
-#'             n.potential.basis.fns = 7)
-#' testDynamic(expr.mat = counts(sce_obj),
-#'             pt = pseudotime_df,
+#' \donttest{
+#' data(sim_counts)
+#' data(sim_pseudotime)
+#' cell_offset <- createCellOffset(sim_counts)
+#' testDynamic(sim_counts,
+#'             pt = sim_pseudotime,
+#'             size.factor.offset = cell_offset,
+#'             genes = sample(rownames(sim_counts), 20))
+#' testDynamic(sim_counts,
+#'             pt = sim_pseudotime,
+#'             size.factor.offset = cell_offset,
 #'             is.gee = TRUE,
-#'             id.vec = colData(sce_obj)$subject_id,
+#'             id.vec = sim_counts$subject,
 #'             cor.structure = "ar1",
-#'             parallel.exec = TRUE,
-#'             n.cores = 8,
-#'             n.potential.basis.fns = 7)
-#' testDynamic(expr.mat = seu_obj,
-#'             pt = pseudotime_df,
-#'             parallel.exec = TRUE,
-#'             n.cores = 8,
+#'             genes = sample(rownames(sim_counts), 20))
+#' testDynamic(sim_counts,
+#'             pt = sim_pseudotime,
+#'             size.factor.offset = cell_offset,
 #'             is.glmm = TRUE,
-#'             id.vec = seu_obj$subject_id)
-#' }
+#'             glmm.adaptive = TRUE,
+#'             id.vec = sim_counts$subject,
+#'             genes = sample(rownames(sim_counts), 20))
+#'}
 
 testDynamic <- function(expr.mat = NULL,
                         pt = NULL,
@@ -98,19 +94,18 @@ testDynamic <- function(expr.mat = NULL,
   }
   if (inherits(expr.mat, "SingleCellExperiment")) {
     expr.mat <- BiocGenerics::counts(expr.mat)[genes, ]
-    expr.mat <- as.matrix(expr.mat)
   } else if (inherits(expr.mat, "Seurat")) {
     expr.mat <- Seurat::GetAssayData(expr.mat,
                                      slot = "counts",
                                      assay = Seurat::DefaultAssay(expr.mat))
-    expr.mat <- as.matrix(expr.mat[genes, ])
+    expr.mat <- expr.mat[genes, ]
   } else if (inherits(expr.mat, "dgCMatrix")) {
-    expr.mat <- as.matrix(expr.mat[genes, ])
+    expr.mat <- expr.mat[genes, ]
   } else {
     expr.mat <- expr.mat[genes, ]
   }
+  expr.mat <- as.matrix(Matrix::t(expr.mat))  # transpose to dense cell x gene matrix
   if (!(inherits(expr.mat, "matrix") || inherits(expr.mat, "array"))) { stop("Input expr.mat must be coerceable to a matrix of integer counts.") }
-  expr.mat <- t(expr.mat)  # transpose to cell x gene matrix
 
   # extract pseudotime dataframe if input is results from Slingshot
   if (inherits(pt, "SlingshotDataSet")) {
diff --git a/data/sim_counts.rda b/data/sim_counts.rda
new file mode 100644
index 0000000..9a28668
Binary files /dev/null and b/data/sim_counts.rda differ
diff --git a/data/sim_pseudotime.rda b/data/sim_pseudotime.rda
new file mode 100644
index 0000000..7e9f9c4
Binary files /dev/null and b/data/sim_pseudotime.rda differ
diff --git a/man/sim_counts.Rd b/man/sim_counts.Rd
new file mode 100644
index 0000000..8d11f2d
--- /dev/null
+++ b/man/sim_counts.Rd
@@ -0,0 +1,19 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/data.R
+\docType{data}
+\name{sim_counts}
+\alias{sim_counts}
+\title{A \code{\link[SingleCellExperiment]{SingleCellExperiment}} object containing simulated counts.}
+\format{
+An object of class \code{\link[SingleCellExperiment]{SingleCellExperiment}}.
+}
+\source{
+https://www.rhondabacher.com/scaffold-vignette.pdf
+}
+\usage{
+data(sim_counts)
+}
+\description{
+Data simulated using the \code{scaffold} R package for 50 dynamic and 50 static genes across 1200 cells from 3 subjects.
+}
+\keyword{datasets}
diff --git a/man/sim_pseudotime.Rd b/man/sim_pseudotime.Rd
new file mode 100644
index 0000000..c75d4ec
--- /dev/null
+++ b/man/sim_pseudotime.Rd
@@ -0,0 +1,19 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/data.R
+\docType{data}
+\name{sim_pseudotime}
+\alias{sim_pseudotime}
+\title{A data.frame containing ground-truth pseudotime.}
+\format{
+An object of class \code{data.frame} with 1200 rows and one variable:
+\itemize{
+ \item PT: the true pseudotime (0.0025--1)
+}
+}
+\usage{
+data(sim_pseudotime)
+}
+\description{
+The true ordering of the 1200 cells contained in \code{sim_counts}.
+}
+\keyword{datasets}
diff --git a/man/testDynamic.Rd b/man/testDynamic.Rd
index e4d043e..37e034c 100644
--- a/man/testDynamic.Rd
+++ b/man/testDynamic.Rd
@@ -66,33 +66,28 @@ This function tests whether a NB \code{marge} model is better than a null (inter
 }
 }
 \examples{
-\dontrun{
-testDynamic(expr.mat = raw_counts,
-            pt = pseudotime_df,
-            parallel.exec = TRUE)
-testDynamic(expr.mat = sce_obj,
-            pt = slingshot_obj,
-            size.factor.offset = sizeFactors(sce_obj),
-            genes = rownames(sce_obj)[1:100])
-testDynamic(expr.mat = raw_counts,
-            pt = pseudotime_df,
-            parallel.exec = TRUE,
-            n.cores = 8,
-            n.potential.basis.fns = 7)
-testDynamic(expr.mat = counts(sce_obj),
-            pt = pseudotime_df,
+\donttest{
+data(sim_counts)
+data(sim_pseudotime)
+cell_offset <- createCellOffset(sim_counts)
+testDynamic(sim_counts,
+            pt = sim_pseudotime,
+            size.factor.offset = cell_offset,
+            genes = sample(rownames(sim_counts), 20))
+testDynamic(sim_counts,
+            pt = sim_pseudotime,
+            size.factor.offset = cell_offset,
             is.gee = TRUE,
-            id.vec = colData(sce_obj)$subject_id,
+            id.vec = sim_counts$subject,
             cor.structure = "ar1",
-            parallel.exec = TRUE,
-            n.cores = 8,
-            n.potential.basis.fns = 7)
-testDynamic(expr.mat = seu_obj,
-            pt = pseudotime_df,
-            parallel.exec = TRUE,
-            n.cores = 8,
+            genes = sample(rownames(sim_counts), 20))
+testDynamic(sim_counts,
+            pt = sim_pseudotime,
+            size.factor.offset = cell_offset,
             is.glmm = TRUE,
-            id.vec = seu_obj$subject_id)
+            glmm.adaptive = TRUE,
+            id.vec = sim_counts$subject,
+            genes = sample(rownames(sim_counts), 20))
 }
 }
 \seealso{