diff --git a/tools/spacexr/.shed.yml b/tools/spacexr/.shed.yml
new file mode 100644
index 00000000000..0b1ac56269b
--- /dev/null
+++ b/tools/spacexr/.shed.yml
@@ -0,0 +1,13 @@
+name: spacexr
+owner: iuc
+description: Cell type identification and cell type-specific differential expression in spatial transcriptomics
+homepage_url: https://github.com/dmcable/spacexr/tree/master
+long_description: Computational methods for cell type identification (RCTD) and differential expression (C-SIDE) on spatial transcriptomics datasets
+remote_repository_url: https://github.com/galaxyproject/tools-iuc/tree/master/tools/spacexr
+categories: 
+- Spatial Omics
+- Single Cell
+suite:
+  name: "suite_spacexr"
+  description: "A suite of Galaxy tools designed to work with the spacexr-tools collection."
+  type: repository_suite_definition
\ No newline at end of file
diff --git a/tools/spacexr/macros.xml b/tools/spacexr/macros.xml
new file mode 100644
index 00000000000..1119d9df3ba
--- /dev/null
+++ b/tools/spacexr/macros.xml
@@ -0,0 +1,104 @@
+<macros>
+    <token name="@TOOL_VERSION@">2.2.1=r43hdfd78af_0</token>
+    <token name="@VERSION_SUFFIX@">0</token>
+    <token name="@PROFILE@">23.0</token>
+    <xml name="requirements">
+        <requirements>
+            <requirement type="package" version="@TOOL_VERSION@">r-spacexr</requirement>
+            <yield/>
+        </requirements>
+    </xml>
+    <xml name="edam">
+        <edam_topics>
+            <edam_topic>topic_4019</edam_topic>
+            <edam_topic>topic_4028</edam_topic>
+            <edam_topic>topic_3308</edam_topic>
+        </edam_topics>
+        <edam_operations>
+            <edam_operation>operation_3223</edam_operation>
+        </edam_operations>
+    </xml>
+    <token name="CSIDE_COMMON_RUN"><![CDATA[
+#if str($type.cell_types) != '':
+cell_types = c($cell_types),
+#end if
+cell_type_threshold = $type.cell_type_threshold,
+gene_threshold = $type.gene_threshold,
+doublet_mode = $type.doublet_mode,
+#if str($type.weight_threshold) != '':
+weight_threshold = $type.weight_threshold,
+#end if
+sigma_gene = $type.sigma_gene,
+PRECISION.THRESHOLD = $type.precision_threshold,
+#if str($type.cell_types_present) != '':
+cell_types_present = c($cell_types_present),
+#end if
+fdr = $type.fdr,
+test_genes_sig = $type.test_genes_sig,
+logs = $type.logs
+    ]]></token>
+    <token name="CSIDE_SINGLE_RUN"><![CDATA[
+myRCTD <- run.CSIDE.single(myRCTD,
+                            explanatory.variable,
+                            normalize_expr = $type.normalize_expr,
+                            log_fc_thresh = $type.log_fc_thresh,
+                            fdr_method = "BH", # default
+                            medv = $type.medv,
+                            CSIDE_COMMON_RUN
+                            )
+    ]]></token>
+    <xml name="sanitizer">
+        <sanitizer invalid_char="">
+            <valid initial="string.ascii_letters,string.digits">
+                <add value="_" />
+            </valid>
+        </sanitizer>
+    </xml>
+    <xml name="patho_barcode" token_help="Comma separated barcodes of the pathological region.">
+        <param name="pathologic_barcode" type="text" optional="false" label="Barcodes" help="@HELP@">
+            <expand macro="sanitizer"/>
+        </param>
+    </xml>
+    <xml name="radius">
+        <param argument="radius" type="integer" min="0" value="50" label="Radius" help="The radius of the exponential filter. Approximately, the distance considered to be a relevant interaction."/>
+    </xml>
+    <xml name="cside_common_input">
+        <param argument="cell_types" type="text" optional="true" label="Cell types used for CSIDE" help="(Comma separated) If null, cell types will be chosen with aggregate occurences of at least 'cell type threshold'."/>
+        <param argument="cell_type_threshold" type="integer" min="0" value="125" label="Cell type threshold" help="Min occurence of number of cells for each cell type to be used."/>
+        <param argument="gene_threshold" type="float" min="0" value="0.00005" label="Gene threshold" help="Minimum average normalized expression required for selecting genes."/>
+        <param argument="doublet_mode" type="boolean" truevalue="TRUE" falsevalue="FALSE" checked="true" label="Use RCTD doublet mode weights?" help="Otherwise, uses RCTD full mode weights." />
+        <param argument="weight_threshold" type="float" min="0" value="" optional="true" label="Weight threshold" help="The threshold of total normalized weights across all cell types in 'cell types' per pixel to be included in the model."/>
+        <param argument="sigma_gene" type="boolean" truevalue="TRUE" falsevalue="FALSE" checked="true" label="Fit gene specific overdispersion parameter?" help="If FALSE, overdispersion parameter is same across all genes." />
+        <param argument="precision_threshold" type="float" min="0" value="0.05" label="Precision threshold" help="For checking for convergence, the maximum parameter change per algorithm step."/>
+        <param argument="cell_types_present" type="text" optional="true" label="Cell types present" help="(Comma separeated) cell types (a superset of 'cell types') to be considered as occuring often enough to consider for gene expression contamination during the step filtering out marker genes of other cell types."/>
+        <param argument="fdr" type="float" min="0" value="0.01" label="FDR" help="False discovery rate for hypothesis testing."/>
+        <param argument="test_genes_sig" type="boolean" truevalue="TRUE" falsevalue="FALSE" checked="true" label="Genes will be tested for significance."/>
+        <param argument="logs" type="boolean" truevalue="TRUE" falsevalue="FALSE" checked="false" label="write progress to log?"/>
+    </xml>
+    <xml name="cside_single_input">
+        <expand macro="cside_common_input"/>
+        <param argument="normalize_expr" type="boolean" truevalue="TRUE" falsevalue="FALSE" checked="false" label="Constrain total gene expression to sum to 1 in each condition?"/>
+        <param argument="log_FC_thresh" type="float" min="0" value="0.4" label="LogFC threshold" help="The natural log fold change cutoff for differential expression."/>
+        <param argument="medv" type="float" min="0" value="0.5" label="Explanatory.variable cutoff" help="For determining if enough pixels for each cell type have explanatory-variable greater than or less than this value."/>
+    </xml>
+    <xml name="output">
+        <section name="output" title="Output Options">
+            <param name="output_selector" type="select" multiple="true" optional="true" display="checkboxes" label="Select / Deselect all">
+                <option value="rds">RDS file</option>
+                <option value="rscript">R script</option>
+                <yield/>
+            </param>
+        </section>
+    </xml>
+    <xml name="citations">
+        <citations>
+            <citation type="doi">10.1038/s41587-021-00830-w</citation>
+            <citation type="doi">10.1038/s41592-022-01575-3</citation>
+            <citation type="bibtex">@Manual{github,
+                title = {SpatialeXpressionR: Cell type identification and cell type-specific differential expression in spatial transcriptomics.},
+                author = {Dylan Cable},
+                url = {https://github.com/dmcable/spacexr}}
+            </citation>
+        </citations>
+    </xml>
+</macros>
\ No newline at end of file
diff --git a/tools/spacexr/spacexr_cside.xml b/tools/spacexr/spacexr_cside.xml
new file mode 100644
index 00000000000..0fa728a2752
--- /dev/null
+++ b/tools/spacexr/spacexr_cside.xml
@@ -0,0 +1,233 @@
+<tool id="spacexr_cside" name="CSIDE" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="@PROFILE@">
+    <description>Cell type-specific differential expression with C-SIDE</description>
+    <macros>
+        <import>macros.xml</import>
+    </macros>
+    <expand macro="edam"/>
+    <expand macro="requirements">
+        <requirement type="package" version="9.0">openssh</requirement>
+    </expand>
+    <command detect_errors="exit_code"><![CDATA[
+        export GALAXY_SLOTS=2 &&
+        mkdir -p 'inputs' 'results' 'logs' 'figures' &&
+        ln -s '$rctd' 'inputs/rctd.rds' &&
+        touch 'results/cside_script.R' &&
+        cat '$cside_script' > 'results/cside_script.R' &&
+        Rscript '$cside_script'
+        #if 'plots' in $output_selector:
+            mv 'results/de_plots/*.pdf' 'results/de_plots_quant/*.pdf' 'results/de_plots_two_regions/*.pdf' 'figures'
+        #end if
+    ]]></command>
+    <configfiles>
+        <configfile name="cside_script"><![CDATA[
+#if $type.cell_types != '':
+    #set $cell_types_list = ['"' + str(x.strip()) + '"' for x in str($type.cell_types).split(',')]
+    #set $cell_types = ','.join($cell_types_list)
+#end if
+#if str($type.cell_types_present) != '':
+    #set $cell_types_present_list = ['"' + str(x.strip()) + '"' for x in str($type.cell_types_present).split(',')]
+    #set $cell_types_present = ','.join($cell_types_present_list)
+#end if
+#if $type.de_type == 'point_density':
+    #set $pathologic_barcode_list = ['"' + str(x.strip()) + '"' for x in str($type.pathologic_barcode).split(',')]
+    #set $pathologic_barcode = ','.join($pathologic_barcode_list)
+#end if
+#if $type.de_type == 'custom':
+    #set $pathologic_barcode_list = ['"' + str(x.strip()) + '"' for x in str($type.pathologic_barcode).split(',')]
+    #set $region_list = [','.join($pathologic_barcode_list)]
+    #for $i, $region in enumerate($type.region):
+        #if str($region.next_pathologic_barcode) != '':
+            #set $next_pathologic_barcode_list = ['"' + str(x.strip()) + '"' for x in str($type.next_pathologic_barcode).split(',')]
+            #set $next_pathologic_barcode = [','.join($next_pathologic_barcode_list)]
+            $region_list.append($next_pathologic_barcode)
+        #end if
+    #end for
+#end if
+
+# cside script
+# This file is used to specify the parameters for the cside from spacexr package
+
+# Load the spacexr library
+library('spacexr')
+library('Matrix')
+library('doParallel')
+
+# load RCTD object
+myRCTD <- readRDS('inputs/rctd.rds')
+core <- Sys.getenv("GALAXY_SLOTS")
+# set core
+
+myRCTD@config[["max_cores"]] <- core
+
+# CSIDE
+#if str($type.de_type) == 'non_parametric':
+myRCTD <- run.CSIDE.nonparam(myRCTD,
+                            df = $type.df,
+                            barcodes = NULL, # use all barcodes
+                            CSIDE_COMMON_RUN
+                            )
+
+#else if str($type.de_type) == 'point_density':
+pathogen_coords <- myRCTD@spatialRNA@coords[c($pathologic_barcode),]
+barcodes <- colnames(myRCTD@spatialRNA@counts)
+explanatory.variable <- exvar.point.density(myRCTD,
+                                            barcodes,
+                                            pathogen_coords,
+                                            radius = $type.radius
+                                            )
+CSIDE_SINGLE_RUN
+
+
+#else if str($type.de_type) == 'cell2cell':
+barcodes <- colnames(myRCTD@spatialRNA@counts)
+explanatory.variable <- exvar.celltocell.interactions(myRCTD,
+                                                        barcodes,
+                                                        '$type.cell_type',
+                                                        radius = $type.radius
+                                                        )
+CSIDE_SINGLE_RUN
+
+
+#else if str($type.de_type) == 'XY':
+    #if str($type.xy) == 'X':
+explanatory.variable <- as.integer(myRCTD@spatialRNA@coords$x &gt; $type.lim)
+names(explanatory.variable) <- rownames(myRCTD@spatialRNA@coords)
+    
+    #else
+explanatory.variable <- as.integer(myRCTD@spatialRNA@coords$y &gt; $type.lim)
+names(explanatory.variable) <- rownames(myRCTD@spatialRNA@coords)
+    #end if
+CSIDE_SINGLE_RUN
+
+#else:
+myRCTD <- run.CSIDE.regions(myRCTD,
+                            $region_list,
+                            log_fc_thresh = $type.log_fc_thresh,
+                            CSIDE_COMMON_RUN
+                            )
+#end if
+
+
+# save the results
+
+# save significant genes in each cell type
+cell_types <- names(myRCTD@de_results[["sig_gene_list"]])
+for (cell_type in cell_types) {
+    df <- myRCTD@de_results[["sig_gene_list"]][[cell_type]]
+    assign(cell_type, df)
+    write.table(df, file = paste0("results/", cell_type, "_sig.tabular"), sep = "\t", quote = FALSE)
+}
+# save all genes in each cell type
+cell_types <- names(myRCTD@de_results[["all_gene_list"]])
+for (cell_type in cell_types) {
+    df <- myRCTD@de_results[["all_gene_list"]][[cell_type]]
+    assign(cell_type, df)
+    write.table(df, file = paste0("results/", cell_type, ".tabular"), sep = "\t", quote = FALSE)
+}
+
+# create plots
+#if 'plots' in $output_selector:
+make_all_de_plots(myRCTD, "figures")
+#end if
+# save rds file
+#if 'rds' in $output_selector:
+saveRDS(myRCTD, file = 'results/cside_results.rds')
+#end if
+        ]]></configfile>
+    </configfiles>
+    <inputs>
+        <param name="rctd" type="data" format="rds" label="RCTD object" help="annotated RCTD object"/>
+        <conditional name="type">
+            <param name="de_type" type="select" label="Type of covariates for explaining differential expression with C-SIDE">
+                <option value="non_parametric">Smooth spatial pattern (non-non_parametric)</option>
+                <option value="point_density">Proximity to pathology</option>
+                <option value="cell2cell">Cell-to-cell interaction</option>
+                <option value="XY">define X or Y axis</option>
+                <option value="custom">Custom spatial locations</option>
+            </param>
+            <when value="non_parametric">
+                <param argument="df" type="integer" min="0" value="15" label="Degrees of freedom" help="The degrees of freedom, or number of basis functions to be used in the model."/>
+                <expand macro="cside_common_input"/>
+            </when>
+            <when value="point_density">
+                <expand macro="patho_barcode"/>
+                <expand macro="radius"/>
+                <expand macro="cside_single_input"/>
+            </when>
+            <when value="cell2cell">
+                <param name="cell_type" type="text" optional="false" label="Cell type for which to compute density">
+                    <expand macro="sanitizer"/>
+                </param>
+                <expand macro="radius"/>
+                <expand macro="cside_single_input"/>
+            </when>
+            <when value="XY">
+                <param name="lim" type="integer" value="" optional="false" label="Axis" help="The number on X or Y axis to discriminate two spatial regions"/>
+                <param name="xy" type="boolean" truevalue="X" falsevalue="Y" checked="true" label="Is the number on X axis?"/>
+                <expand macro="cside_single_input"/>
+            </when>
+            <when value="custom">
+                <expand macro="patho_barcode" help="Comma separated barcodes of the custom region."/>
+                <repeat name="region" min="0" title="Next custom region">
+                    <param name="next_pathologic_barcode" type="text" optional="false" label="Barcodes" help="Comma separated barcodes of the custom region.">
+                        <expand macro="sanitizer"/>
+                    </param>
+                </repeat>
+                <expand macro="cside_common_input"/>
+                <param argument="log_FC_thresh" type="float" min="0" value="0.4" label="logFC cutoff for differential expression"/>
+            </when>
+        </conditional>
+        <expand macro="output">
+            <option value="plots">DEG plots</option>
+        </expand>
+    </inputs>
+    <outputs>
+        <collection name="de_results" type="list" label="${tool.name} on ${on_string}: DE Results">
+            <discover_datasets pattern="(?P&lt;name&gt;.+)\.tabular$" format="tabular" directory="results"/>
+        </collection>
+        <collection name="de_plots" type="list" label="${tool.name} on ${on_string}: DE plots">
+            <discover_datasets pattern="(?P&lt;name&gt;.+)\.pdf$" format="pdf" directory="figures"/>
+            <filter>output['output_selector'] and 'plots' in output['output_selector']</filter>
+        </collection>
+        <data name="out_rds" format="rds" from_work_dir="results/cside_results.rds" label="${tool.name} on ${on_string}: RDS file">
+            <filter>output['output_selector'] and 'rds' in output['output_selector']</filter>
+        </data>
+        <data name="out_rscript" format="txt" from_work_dir="results/cside_script.R" label="${tool.name} on ${on_string}: RScript">
+            <filter>output['output_selector'] and 'rscript' in output['output_selector']</filter>
+        </data>
+    </outputs>
+    <tests>
+        <test expect_num_outputs="2">
+            <param name="rctd" value="myRCTD_merfish.rds"/>
+            <param name="de_type" value="non_parametric"/>
+            <param name="cell_types" value="Astrocytes"/>
+            <param name="cell_type_threshold" value="10"/>
+            <param name="gene_threshold" value="0.001"/>
+            <param name="fdr" value="0.25"/>
+            <param name="output_selector" value="rscript" />
+            <output_collection name="de_results" type="list">
+                <element name="type8" ftype="tabular">
+                    <assert_contents>
+                        <has_text_matching expression="Hello"/>
+                    </assert_contents>
+                </element>
+                <element name="type8_sig" ftype="tabular">
+                    <assert_contents>
+                        <has_text_matching expression="Hello"/>
+                    </assert_contents>
+                </element>
+            </output_collection>
+            <output name="out_rscript">
+                <assert_contents>
+                    <has_text_matching expression="run.CSIDE.nonparam"/>
+                </assert_contents>
+            </output>
+        </test>
+    </tests>
+    <help><![CDATA[
+
+Cell type-Specific Inference of Differential Expression, or CSIDE, is part of the spacexr R package for learning cell type-specific differential expression from spatial transcriptomics data.
+
+    ]]></help>
+    <expand macro="citations" />
+</tool>
\ No newline at end of file
diff --git a/tools/spacexr/spacexr_rctd.xml b/tools/spacexr/spacexr_rctd.xml
new file mode 100644
index 00000000000..b7d7d7a18b6
--- /dev/null
+++ b/tools/spacexr/spacexr_rctd.xml
@@ -0,0 +1,377 @@
+<tool id="spacexr_rctd" name="RCTD" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="@PROFILE@">
+    <description>Cell type identification with RCTD</description>
+    <macros>
+        <import>macros.xml</import>
+    </macros>
+    <expand macro="edam"/>
+    <expand macro="requirements"/>
+    <command detect_errors="exit_code"><![CDATA[
+        mkdir -p 'results' 'figures' 'inputs' &&
+        ln -s '$sc_count' 'inputs/sc_count.tabular' &&
+        ln -s '$metadata' 'inputs/metadata.tabular' &&
+        ln -s '$st_count' 'inputs/st_count.tabular' &&
+        ln -s '$coord' 'inputs/coords.tabular' &&
+        touch 'results/rctd_script.R' &&
+        cat '$rctd_script' > 'results/rctd_script.R' &&
+        Rscript '$rctd_script'
+    ]]></command>
+    <configfiles>
+        <configfile name="rctd_script"><![CDATA[
+# rctd script
+# This file is used to specify the parameters for the rctd from spacexr package
+
+# Load the spacexr library
+library('spacexr')
+library('Matrix')
+
+### Load the scRNA-seq data
+counts <- read.table(file = 'inputs/sc_count.tabular', row.names = 1, sep = '\t', header = T)
+metadata <- read.table(file = 'inputs/metadata.tabular', sep = '\t', header = T)
+
+# create cell_types named list
+cell_types <- metadata[,"annotation"]; names(cell_types) <- metadata[,"barcode"]
+
+# convert to factor data type
+cell_types <- as.factor(cell_types)
+
+#if str($sc_umi_input) == 'True':
+# create nUMI named list
+nUMI <- metadata[, "nUMI"]; names(nUMI) <- metadata[,"barcode"]
+#end if
+
+# Create reference object
+reference <- Reference(
+                    counts = counts,
+                    cell_types = cell_types,
+                    #if str($sc_umi_input) == 'True':
+                        nUMI = nUMI,
+                    #end if
+                    n_max_cells = $n_max_cells,
+                    min_UMI = $min_UMI
+                    )
+
+### Load spatial data
+counts <- read.table(file = 'inputs/st_count.tabular', row.names = 1, sep = '\t', header = T)
+coords <- read.table(file = 'inputs/coords.tabular', row.names = 1, sep = '\t', header = T)
+
+nUMI <- colSums(counts) # In tutorials it is always the sum of counts
+
+# Create SpatialRNA object
+puck <- SpatialRNA(
+                coords = coords,
+                counts = counts,
+                nUMI= nUMI,
+                )
+
+# provide a basic plot of the nUMI of each pixel on the plot:
+pdf('figures/nUMI_plot.pdf')
+plot_puck_continuous(
+    puck = puck,
+    barcodes = colnames(puck@counts),
+    plot_val = puck@nUMI,
+    ylimit = c(0,round(quantile(puck@nUMI,0.9))),
+    title ='plot of nUMI')
+dev.off()
+
+### Run the RCTD
+myRCTD <- create.RCTD(
+                spatialRNA = puck,
+                reference = reference,
+                gene_cutoff = $gene_cutoff,
+                fc_cutoff = $fc_cutoff,
+                gene_cutoff_reg = $gene_cutoff_reg,
+                fc_cutoff_reg = $fc_cutoff_reg,
+                UMI_min = $umi_min,
+                UMI_max = $umi_max,
+                counts_MIN = $counts_min,
+                UMI_min_sigma = $umi_min_sigma,
+                class_df = NULL, # set as default
+                CELL_MIN_INSTANCE = $cell_min_instance,
+                #if str($cell_type_names) != "":
+                    cell_type_names = $cell_type_names,
+                #end if                            
+                MAX_MULTI_TYPES = $max_multi_types,
+                keep_reference = F, # set as default
+                cell_type_profiles = NULL, # set as default
+                CONFIDENCE_THRESHOLD = $confidence_threshold,
+                DOUBLET_THRESHOLD = $doublet_threshold,)
+
+myRCTD <- run.RCTD(
+                myRCTD,
+                doublet_mode = "$doublet_mode")
+
+
+# save results
+#if str($doublet_mode) == 'doublet':
+results <- myRCTD@results
+
+# save the data frame
+result_df <- results["results_df"]
+write.table(result_df, file = 'results/doublet_results_df.tabular', sep = '\t', quote = F, row.names = T)
+
+# RCTD plots
+# normalize the cell type proportions to sum to 1.
+norm_weights <- normalize_weights(results[["weights"]])
+cell_type_names <- myRCTD@cell_type_info[["info"]][[2]] #list of cell type names
+spatialRNA <- myRCTD@spatialRNA
+
+resultsdir <- 'figures'
+
+# make the plots
+# Plots the confident weights for each cell type as in full_mode (saved as 'figures/cell_type_weights.pdf')
+plot_weights(cell_type_names, spatialRNA, resultsdir, norm_weights) 
+
+# Plots all weights for each cell type as in full_mode. (saved as 'figures/cell_type_weights_unthreshold.pdf')
+plot_weights_unthreshold(cell_type_names, spatialRNA, resultsdir, norm_weights) 
+
+# Plots the weights for each cell type as in doublet_mode. (saved as 'figures/cell_type_weights_doublets.pdf')
+plot_weights_doublet(cell_type_names, spatialRNA, resultsdir, results[["weights_doublet"]],results[["results_df"]])
+
+# Plots the number of confident pixels of each cell type in 'full_mode'. (saved as 'figures/cell_type_occur.pdf')
+plot_cond_occur(cell_type_names, resultsdir, norm_weights, spatialRNA)
+
+# makes a map of all cell types, (saved as 'figures/all_cell_types.pdf')
+plot_all_cell_types(results[["results_df"]], spatialRNA@coords, cell_type_names, resultsdir) 
+
+# doublets
+#obtain a dataframe of only doublets
+doublets <- results[["results_df"]][results[["results_df"]][["spot_class"]] == "doublet_certain",] 
+
+# Plots all doublets in space (saved as 'figures/all_doublets.pdf')
+plot_doublets(spatialRNA, doublets, resultsdir, cell_type_names)
+
+# Plots all doublets in space for each cell type (saved as 'figures/all_doublets_type.pdf')
+plot_doublets_type(spatialRNA, doublets, resultsdir, cell_type_names) 
+
+# a table of frequency of doublet pairs 
+doub_occur <- table(doublets[["second_type"]], doublets[["first_type"]]) 
+# Plots a stacked bar plot of doublet ocurrences (saved as 'figures/doublet_stacked_bar.pdf')
+plot_doub_occur_stack(doub_occur, resultsdir, cell_type_names) 
+#end if
+
+#if str($doublet_mode) == 'full':
+results <- myRCTD@results
+
+# RCTD plots
+# normalize the cell type proportions to sum to 1.
+norm_weights <- normalize_weights(results[["weights"]])
+cell_type_names <- myRCTD@cell_type_info[["info"]][[2]] #list of cell type names
+spatialRNA <- myRCTD@spatialRNA
+
+resultsdir <- 'figures'
+
+# make the plots
+# Plots the confident weights for each cell type as in full_mode (saved as 'figures/cell_type_weights.pdf')
+plot_weights(cell_type_names, spatialRNA, resultsdir, norm_weights) 
+
+# Plots all weights for each cell type as in full_mode. (saved as 'figures/cell_type_weights_unthreshold.pdf')
+plot_weights_unthreshold(cell_type_names, spatialRNA, resultsdir, norm_weights) 
+
+# Plots the number of confident pixels of each cell type in 'full_mode'. (saved as 'figures/cell_type_occur.pdf')
+plot_cond_occur(cell_type_names, resultsdir, norm_weights, spatialRNA)
+#end if
+
+#if str($doublet_mode) == 'multi':
+sink('results/multi_results.txt')
+# Loop through all elements in "myRCTD@results"
+for (i in seq_along(myRCTD@results)) {
+cat('Examining results on pixel / spot', i, '\n')
+
+pixel <- myRCTD@results[[i]]  # Access the ith pixel
+
+cat('Check convergence:\n')
+print(pixel[["conv_sub"]])
+
+cat('Check cell types:\n')
+print(pixel[["cell_type_list"]])
+
+cat('Check confidence:\n')
+print(pixel[["conf_list"]])
+
+cat('Check weights:\n')
+print(pixel[["sub_weights"]])
+
+cat('\n')
+}
+sink()
+#end if
+
+# save rds file
+#if 'rds' in $output_selector:
+saveRDS(myRCTD, file = 'results/rctd_results.rds')
+#end if
+        ]]></configfile>
+    </configfiles>
+    <inputs>
+        <param name="sc_count" type="data" format="tabular" label="Single-cell count matrix" help="A matrix representing Digital Gene Expression (DGE). Rownames should be genes and colnames represent barcodes/cell names" />
+        <param name="metadata" type="data" format="tabular" label="Metadata" help="single-cell annotation file with columns: barcode, annotation, and nUMI(optional)" />
+        <param name="sc_umi_input" type="boolean" truevalue="True" falsevalue="False" checked="false" label="nUMI" help="Does your single-cell metadata have nUMI column?" />
+        <param name="st_count" type="data" format="tabular" label="Spatial count matrix" help="A matrix representing Digital Gene Expression (DGE). Rownames should be genes and colnames represent barcodes/pixel names" />
+        <param name="coord" type="data" format="tabular" label="Spatial coordinates" help="A numeric table representing the spatial pixel locations. Rownames are barcodes/pixel names, and there should be two columns for x and for y" />
+        <param name="doublet_mode" type="select" label="Doublet mode">
+            <option value="doublet">doublet</option>
+            <option value="full">full</option>
+            <option value="multi">multi</option>
+        </param>
+        <section name="advanced_param" title="Advanced parameters">
+            <section name="ref_param" title="Reference object parameters">
+                <param argument="n_max_cells" type="integer" min="0" value="10000" label="Maximum number of cells per cell type" help="Will downsample if this number is exceeded." />
+                <param argument="min_UMI" type="integer" min="0" value="100" label="Minimum UMI count for cells to be included in the reference"/>
+            </section>
+            <section name="st_param" title="SpatialRNA object parameters">
+                <param argument="gene_cutoff" type="float" min="0" value="0.000125" label="Gene cutoff" help="Minimum normalized gene expression for genes to be included in the platform effect normalization step." />
+                <param argument="fc_cutoff" type="float" min="0" value="0.5" label="logFC cutoff" help="Minimum log-fold-change (across cell types) for genes to be included in the platform effect normalization step." />
+                <param argument="gene_cutoff_reg" type="float" min="0" value="0.0002" label="Gene cutoff-reg" help="Minimum normalized gene expression for genes to be included in the RCTD step." />
+                <param argument="fc_cutoff_reg" type="float" min="0" value="0.75" label="logFC cutoff-reg" help="Minimum log-fold-change (across cell types) for genes to be included in the RCTD step." />
+                <param argument="umi_min" type="integer" min="0" value="100" label="Minimum UMI per pixel"/>
+                <param argument="umi_max" type="integer" min="0" value="20000000" label="Maximum UMI per pixel"/>
+                <param argument="counts_min" type="integer" min="0" value="10" label="Minimum total counts per pixel"/>
+                <param argument="umi_min_sigma" type="integer" min="0" value="300" label="Minimum UMI per pixel for the choose_sigma_c function"/>
+                <param argument="cell_min_instance" type="integer" min="0" value="25" label="Minimum number of cells per cell type"/>
+                <param argument="cell_type_names" type="text" value="" label="Cell types to be included from the reference" help="A comma separated list. If NULL, uses all cell types">
+                    <expand macro="sanitizer"/>
+                </param>
+                <param argument="max_multi_types" type="integer" min="0" value="4" label="Max number of cell types per pixel"/>
+                <param argument="confidence_threshold" type="integer" min="0" value="5" label="Confidence threshold" help="The minimum change in likelihood (compared to other cell types) necessary to determine a cell type identity with confidence." />
+                <param argument="doublet_threshold" type="integer" min="0" value="20" label="Doublet threshold" help="The penalty weight of predicting a doublet instead of a singlet for a pixel." />
+            </section>
+        </section>
+        <expand macro="output"/>
+    </inputs>
+    <outputs>
+        <collection name="out_fig" type="list" label="${tool.name} on ${on_string}: Spacexr Results">
+            <discover_datasets pattern="(?P&lt;name&gt;.+)\.pdf$" format="pdf" directory="figures/"/>
+        </collection>
+
+        <data name="out_doublet_df" format="tabular" from_work_dir="results/doublet_results_df.tabular" label="${tool.name} on ${on_string}: Doublet result table">
+            <filter>doublet_mode == 'doublet'</filter>
+        </data>
+
+        <data name="out_multi" format="txt" from_work_dir="results/multi_results.txt" label="${tool.name} on ${on_string}: multi result">
+            <filter>doublet_mode == 'multi'</filter>
+        </data>
+        <data name="out_rds" format="rds" from_work_dir="results/rctd_results.rds" label="${tool.name} on ${on_string}: RDS file">
+            <filter>output['output_selector'] and 'rds' in output['output_selector']</filter>
+        </data>
+        <data name="out_rscript" format="txt" from_work_dir="results/rctd_script.R" label="${tool.name} on ${on_string}: RScript">
+            <filter>output['output_selector'] and 'rscript' in output['output_selector']</filter>
+        </data>
+    </outputs>
+    <tests>
+        <test expect_num_outputs="4">
+            <param name="sc_count" value="sc_count.tabular"/>
+            <param name="metadata" value="metadata.tabular"/>
+            <param name="sc_umi_input" value="True"/>
+            <param name="st_count" value="st_count.tabular"/>
+            <param name="coord" value="coords.tabular"/>
+            <param name="doublet_mode" value="doublet"/>
+            <param name="output_selector" value="rds,rscript" />
+            <output_collection name="out_fig" type="list">
+                <element name="all_cell_types" file="all_cell_types_d.pdf" ftype="pdf" compare="sim_size"/>
+                <element name="all_doublets" file="all_doublets_d.pdf" ftype="pdf" compare="sim_size"/>
+                <element name="all_doublets_type" file="all_doublets_type_d.pdf" ftype="pdf" compare="sim_size"/>
+                <element name="cell_type_occur" file="cell_type_occur_d.pdf" ftype="pdf" compare="sim_size"/>
+                <element name="cell_type_weights" file="cell_type_weights_d.pdf" ftype="pdf" compare="sim_size"/>
+                <element name="cell_type_weights_doublets" file="cell_type_weights_doublets_d.pdf" ftype="pdf" compare="sim_size"/>
+                <element name="cell_type_weights_unthreshold" file="cell_type_weights_unthreshold_d.pdf" ftype="pdf" compare="sim_size"/>
+                <element name="doublet_stacked_bar" file="doublet_stacked_bar_d.pdf" ftype="pdf" compare="sim_size"/>
+                <element name="nUMI_plot" file="nUMI_plot.pdf" ftype="pdf" compare="sim_size"/>
+            </output_collection>
+            <output name="out_doublet_df">
+                <assert_contents>
+                    <has_text_matching expression="results_df.spot_class\tresults_df.first_type\tresults_df.second_type\tresults_df.first_class\tresults_df.second_class\tresults_df.min_score\tresults_df.singlet_score\tresults_df.conv_all\tresults_df.conv_doublet"/>
+                    <has_text_matching expression="CACGGCCATATTGC\tsinglet\ttype10\ttype6\tFALSE\tFALSE\t228.242919161702\t237.523081507358\tTRUE\tTRUE"/>
+                </assert_contents>
+            </output>
+            <output name="out_rds" file="rds_doublet.rds" compare="sim_size"/>
+            <output name="out_rscript">
+                <assert_contents>
+                    <has_text text="library('spacexr')"/>
+                    <has_text text="nUMI &lt;- metadata[, &quot;nUMI&quot;]"/>
+                    <has_text text="doublet_mode = &quot;doublet&quot;"/>
+                </assert_contents>
+            </output>
+        </test>
+        <test expect_num_outputs="3">
+            <param name="sc_count" value="sc_count.tabular"/>
+            <param name="metadata" value="metadata.tabular"/>
+            <param name="sc_umi_input" value="False"/>
+            <param name="st_count" value="st_count.tabular"/>
+            <param name="coord" value="coords.tabular"/>
+            <param name="doublet_mode" value="full"/>
+            <param name="output_selector" value="rds,rscript" />
+            <output_collection name="out_fig" type="list">
+                <element name="cell_type_occur" file="cell_type_occur_f.pdf" ftype="pdf" compare="sim_size"/>
+                <element name="cell_type_weights" file="cell_type_weights_f.pdf" ftype="pdf" compare="sim_size"/>
+                <element name="cell_type_weights_unthreshold" file="cell_type_weights_unthreshold_f.pdf" ftype="pdf" compare="sim_size"/>
+                <element name="nUMI_plot" file="nUMI_plot.pdf" ftype="pdf" compare="sim_size"/>
+            </output_collection>
+            <output name="out_rds" file="rds_full.rds" compare="sim_size"/>
+            <output name="out_rscript">
+                <assert_contents>
+                    <has_text text="library('spacexr')"/>
+                    <not_has_text text="nUMI &lt;- metadata[, &quot;nUMI&quot;]"/>
+                    <has_text text="doublet_mode = &quot;full&quot;"/>
+                </assert_contents>
+            </output>
+        </test>
+        <test expect_num_outputs="4">
+            <param name="sc_count" value="sc_count.tabular"/>
+            <param name="metadata" value="metadata.tabular"/>
+            <param name="sc_umi_input" value="False"/>
+            <param name="st_count" value="st_count.tabular"/>
+            <param name="coord" value="coords.tabular"/>
+            <param name="doublet_mode" value="multi"/>
+            <param name="output_selector" value="rds,rscript" />
+            <output_collection name="out_fig" type="list">
+                <element name="nUMI_plot" file="nUMI_plot.pdf" ftype="pdf" compare="sim_size"/>
+            </output_collection>
+            <output name="out_multi">
+                <assert_contents>
+                    <has_text text="Examining results on pixel / spot 1"/>
+                    <has_text text="Check convergence:"/>
+                    <has_text text="[1] TRUE"/>
+                    <has_text text="Check cell types:"/>
+                    <has_text text="[1] &quot;type18&quot; &quot;type6&quot;"/>
+                    <has_text text="Check confidence:"/>
+                    <has_text text="Check weights:"/>
+                </assert_contents>
+            </output>
+            <output name="out_rds" file="rds_multi.rds" compare="sim_size"/>
+            <output name="out_rscript">
+                <assert_contents>
+                    <has_text text="library('spacexr')"/>
+                    <not_has_text text="nUMI &lt;- metadata[, &quot;nUMI&quot;]"/>
+                    <has_text text="doublet_mode = &quot;multi&quot;"/>
+                </assert_contents>
+            </output>
+        </test>
+    </tests>
+    <help><![CDATA[
+
+Robust Cell Type Decomposition, or **RCTD**, is an statistical method for learning cell types from spatial transcriptomics data.
+
+**Reference object**:
+
+To create the single-cell reference object, the following inputs are required:
+    * counts: A matrix representing Digital Gene Expression (DGE). **Rownames** should be genes and **colnames** represent barcodes/cell names. Counts should be **untransformed** count-level data.
+    * cell_types: A named (by cell barcode) factor of cell type for each cell.
+    * nUMI: Optional, a named (by cell barcode) list of total counts or UMI&apos;s appearing at each cell. If not provided, nUMI will be assumed to be the total counts appearing on each cell. 
+
+**SpatialRNA object**:
+
+To create the spatialRNA object, the following inputs are required:
+    * coords: A numeric table representing the spatial pixel locations. **Rownames** are barcodes/pixel names, and there should be two columns for **x** and for **y**.
+    * counts: A matrix representing Digital Gene Expression (DGE). **Rownames** should be genes and **colnames** represent barcodes/pixel names. Counts should be **untransformed** count-level data.
+
+-----
+
+RCTD has **three** modes:
+    * **doublet mode**, which assigns 1-2 cell types per spot and is recommended for technologies with high spatial resolution such as Slide-seq and MERFISH.
+    * **full mode**, which assigns any number of cell types per spot and is recommended for technologies with poor spatial resolution such as 100-micron resolution Visium.
+    * **multi mode**, an extension of doublet mode that can discover more than two cell types per spot (3-4 cell types) as an alternative option to full mode.
+
+    ]]></help>
+
+    <expand macro="citations" />
+</tool>
\ No newline at end of file
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diff --git a/tools/spacexr/test-data/coords.tabular b/tools/spacexr/test-data/coords.tabular
new file mode 100644
index 00000000000..8b0c38f375c
--- /dev/null
+++ b/tools/spacexr/test-data/coords.tabular
@@ -0,0 +1,101 @@
+xcoord	ycoord
+TTGGACGTTTCAAT	3411.272727	2254.628099
+CACGGCCATATTGC	4613.2	1476.2
+CGCCCCCCACCCCT	4707.967742	1408.806452
+CCCCCCCCATTGAA	5149.506329	2548.746835
+CGCTTGGCATTTAC	4121.015625	2071.171875
+CGTGAGTTTCTCCT	4015.358491	2927.792453
+ATTCAGTCGCATTA	1999.537037	4174.777778
+CCAACTCCCCTACT	4146.134328	1226.731343
+TTAAGGCCTAGGCT	4282.266055	2882.779817
+GACCTTCAGAGTAA	1661.597826	3514.98913
+TGAAGGTTTTATGC	1781.770115	4430.333333
+GCCGGATCTTCTTT	4605.227723	1490.425743
+AACAGCGTTCCTTG	1920.569231	4403.169231
+CTTCAAACATGTCA	4087.70073	3249.343066
+AGACCCCCACGCCG	2065.982456	3026.596491
+AAGTACCCGCCCTG	4574.882883	2635.216216
+ACTCTTGCTCGCGC	3342.57377	1449.278689
+GTAACCTAGATCTG	1606.680672	3603.932773
+GTCATAACGACAGG	1799.530864	4008.209877
+TGTATCTCCGAGTG	4975.697674	1796.488372
+TCCAGCTGTTCGAA	4133.957983	3144.487395
+GAACATGGGTATTG	5168.25	2557.789474
+GCCAGTATCCGAAG	1681.010417	3540.958333
+TGTTGTAGCTAAAG	3110	1160.2625
+ATGCCTCAGTCCTG	2158.158879	4057.831776
+ATAGGATATATCTT	3095.28972	1160.570093
+TGCCTATATTACGC	3561.372222	1309.95
+ATTTGGACGCATGC	3930.07563	3016.840336
+AAGCCCCCCGAGCC	5354.777778	2220.722222
+GTTAGGCGTCCCGC	5168.90566	1792.528302
+CAGCGGGCGATTCC	2399.760274	3199.130137
+TAGGGTGGGCTGTA	1275.543689	3729.048544
+GGGGACGAATAGTG	1670.946903	3814.619469
+CTCTCCTCATGTCT	3284.637037	1350.407407
+GTAGATACAGATTC	4113.824176	2797.21978
+CGGAAACTTGACAC	2876.798246	2457.254386
+GATCCTGCATTGTT	2434.157895	4509.789474
+TAAGGGTAGATTTT	3748.984375	2247.53125
+GGCTCGAGTTTAAG	2865.632353	2317.536765
+CTGGTTTCCCCTTG	2248.035461	3062.652482
+TCTTACCATCAGTG	5127.96748	1642.552846
+AGGAGGGTCCATTT	2464.95098	2829.303922
+TTTGATACGCCAGT	2150.886792	4174.924528
+TTGACCGTTCTTCC	4247.308333	1194.733333
+TTCTCAGTCTCCTT	1762.921348	4606.179775
+CATTTAATGTCGTG	2114.673913	3097.391304
+CCCTTTCACAGCGA	2836.63964	2440.351351
+CCTACCAAAGCTCT	4175.059524	3299.071429
+AGAGGTTATCTCGA	3395.877049	2251.434426
+TAATCGGAAGACTC	5275.656716	2485.716418
+CTTGCACCTAGAAC	2047.038095	3076.914286
+TACGGACAGTTACT	1805.061856	4818.597938
+AATACTCACTCATT	3014.676056	1278.267606
+GGCCTAACTCCACA	5158.376812	2345.985507
+GCCCCGGAATCCCT	2027.621359	3997.533981
+TCCCACGCCGCGTG	2361.92437	4474.848739
+TACGGGTCAGTTCC	2481.358491	2756.726415
+TATCTCCGTGCAAC	1599.376623	3992.935065
+TGTAGGCTTCCCTT	3829.141176	2279.823529
+GTCTGAGCACTGTC	2105.425926	2405.981481
+TATTGCATCTCTGT	3557.809524	2408.301587
+TAGCACATAATCCC	4061.595588	2322.919118
+AAGCCTGACCGCAC	4792.901961	2133.441176
+GTATGGAGCATACT	1797.816327	4695.693878
+CAAACATGAGATTC	1305.457447	3790.117021
+GTTTCCAATATTAG	2111.26087	3710.855072
+CGGCTCCGTAGAAC	5339.189655	2420.068966
+TAAGTTGTGAGGCC	2620.84	2727.95
+GTGCCCCTATCCTG	4556.195876	2072.381443
+ATGTGCCACATCGG	4272.132075	3162.113208
+CCGCCGTCTCGATG	2929.590909	2225.386364
+GAACTCAGTCTTGA	2903.031579	2275.842105
+CAGCTCGTGCTTGA	4204.92381	1336.009524
+GGCTGGCTGAGGCC	2397.481481	3388.055556
+TAGGCTGAAGACTG	3113.294737	1122.021053
+CTTCCGGCATGTCC	3792.613139	2258.642336
+GCCCCCCATCTGCT	3344.559748	1374.283019
+GATTGGTCCGGCTG	4056.47619	3032.642857
+CCGATTGGAGATCA	4183.17757	1716.757009
+AGCTTATTACGTTG	5264.564103	2472.525641
+TGGCCTGGTTATCC	1370.680851	4172.585106
+AAGGTATCTCAACA	3282.604651	1526.162791
+CGTTACACACCTCA	2070.391304	4560.086957
+TGGTTGAGCGATCT	1622.819277	4424.759036
+GTGGAACCAGCCAA	4201.067961	3413.708738
+GTTCTTAGATCCTT	1812.477273	3575.977273
+CGGCCGTGCCCACC	3168.758333	2117.741667
+TTCTGGTTTCTGGC	2307.728814	4313.067797
+CTGATTGTGCTCAT	5287.342105	2475.684211
+CACATATGCCTCCT	4344.443038	2733.924051
+TATCTGTGAAGGAC	2047.981651	3715.33945
+TGACATATTCATCT	3550.040404	1268.929293
+CGGCTGGCTCGACC	4960.953488	1695.197674
+AAGGCTCTACATCA	2030.6	2340.095238
+TATGCCCAGGACAG	3920.147541	3439.02459
+ATGAGTCCACATCT	4251.160584	1528.839416
+ATCTTTCCTTCAAA	5021.540541	2466.378378
+TAGTCCCCATCCGC	4955.401575	1479.582677
+ACACTGATCTTGTC	3080.92126	1837.023622
+CTTTTGCTCCGGAA	4737.852459	1814.639344
diff --git a/tools/spacexr/test-data/doublet.R b/tools/spacexr/test-data/doublet.R
new file mode 100644
index 00000000000..cc22073f313
--- /dev/null
+++ b/tools/spacexr/test-data/doublet.R
@@ -0,0 +1,126 @@
+
+            # rctd script
+            # This file is used to specify the parameters for the rctd from spacexr package
+
+            # Load the spacexr library
+            library('spacexr')
+            library('Matrix')
+
+            counts <- read.table(file = 'inputs/sc_count.tabular', row.names = 1, sep = '\t', header = T)
+            metadata <- read.table(file = 'inputs/metadata.tabular', sep = '\t', header = T)
+
+            # create cell_types named list
+            cell_types <- metadata[,"annotation"]; names(cell_types) <- metadata[,"barcode"]
+            
+            # convert to factor data type
+            cell_types <- as.factor(cell_types)
+
+                # create nUMI named list
+                nUMI <- metadata[, "nUMI"]; names(nUMI) <- metadata[,"barcode"]
+
+            # Create reference object
+            reference <- Reference(
+                                counts = counts,
+                                cell_types = cell_types,
+                                    nUMI = nUMI,
+                                n_max_cells = 10000,
+                                min_UMI = 100
+                                )
+
+            counts <- read.table(file = 'inputs/st_count.tabular', row.names = 1, sep = '\t', header = T)
+            coords <- read.table(file = 'inputs/coords.tabular', row.names = 1, sep = '\t', header = T)
+
+            nUMI <- colSums(counts) # In tutorials it is always the sum of counts
+
+            # Create SpatialRNA object
+            puck <- SpatialRNA(
+                            coords = coords,
+                            counts = counts,
+                            nUMI= nUMI,
+                            )
+
+            # provide a basic plot of the nUMI of each pixel on the plot:
+            pdf('figures/nUMI_plot.pdf')
+            plot_puck_continuous(
+                puck = puck,
+                barcodes = colnames(puck@counts),
+                plot_val = puck@nUMI,
+                ylimit = c(0,round(quantile(puck@nUMI,0.9))),
+                title ='plot of nUMI')
+            dev.off()
+
+            myRCTD <- create.RCTD(
+                            spatialRNA = puck,
+                            reference = reference,
+                            gene_cutoff = 0.000125,
+                            fc_cutoff = 0.5,
+                            gene_cutoff_reg = 0.0002,
+                            fc_cutoff_reg = 0.75,
+                            UMI_min = 100,
+                            UMI_max = 20000000,
+                            counts_MIN = 10,
+                            UMI_min_sigma = 300,
+                            class_df = NULL, # set as default
+                            CELL_MIN_INSTANCE = 25,
+                            MAX_MULTI_TYPES = 4,
+                            keep_reference = F, # set as default
+                            cell_type_profiles = NULL, # set as default
+                            CONFIDENCE_THRESHOLD = 5,
+                            DOUBLET_THRESHOLD = 20,)
+
+            myRCTD <- run.RCTD(
+                            myRCTD,
+                            doublet_mode = "doublet")
+
+
+            # save results
+                results <- myRCTD@results
+
+                # save the data frame
+                result_df <- results["results_df"]
+                write.table(result_df, file = 'results/doublet_results_df.tabular', sep = '\t', quote = F, row.names = T)
+
+                # RCTD plots
+                # normalize the cell type proportions to sum to 1.
+                norm_weights <- normalize_weights(results[["weights"]])
+                cell_type_names <- myRCTD@cell_type_info[["info"]][[2]] #list of cell type names
+                spatialRNA <- myRCTD@spatialRNA
+
+                resultsdir <- 'figures'
+                
+                # make the plots
+                # Plots the confident weights for each cell type as in full_mode (saved as 'figures/cell_type_weights.pdf')
+                plot_weights(cell_type_names, spatialRNA, resultsdir, norm_weights) 
+                
+                # Plots all weights for each cell type as in full_mode. (saved as 'figures/cell_type_weights_unthreshold.pdf')
+                plot_weights_unthreshold(cell_type_names, spatialRNA, resultsdir, norm_weights) 
+                
+                # Plots the weights for each cell type as in doublet_mode. (saved as 'figures/cell_type_weights_doublets.pdf')
+                plot_weights_doublet(cell_type_names, spatialRNA, resultsdir, results[["weights_doublet"]],results[["results_df"]])
+
+                # Plots the number of confident pixels of each cell type in 'full_mode'. (saved as 'figures/cell_type_occur.pdf')
+                plot_cond_occur(cell_type_names, resultsdir, norm_weights, spatialRNA)
+
+                # makes a map of all cell types, (saved as 'figures/all_cell_types.pdf')
+                plot_all_cell_types(results[["results_df"]], spatialRNA@coords, cell_type_names, resultsdir) 
+
+                # doublets
+                #obtain a dataframe of only doublets
+                doublets <- results[["results_df"]][results[["results_df"]][["spot_class"]] == "doublet_certain",] 
+                
+                # Plots all doublets in space (saved as 'figures/all_doublets.pdf')
+                plot_doublets(spatialRNA, doublets, resultsdir, cell_type_names)
+            
+                # Plots all doublets in space for each cell type (saved as 'figures/all_doublets_type.pdf')
+                plot_doublets_type(spatialRNA, doublets, resultsdir, cell_type_names) 
+                
+                # a table of frequency of doublet pairs 
+                doub_occur <- table(doublets[["second_type"]], doublets[["first_type"]]) 
+                # Plots a stacked bar plot of doublet ocurrences (saved as 'figures/doublet_stacked_bar.pdf')
+                plot_doub_occur_stack(doub_occur, resultsdir, cell_type_names) 
+            
+
+
+            # save rds file
+                saveRDS(myRCTD, file = 'results/rctd_results.rds')
+        
\ No newline at end of file
diff --git a/tools/spacexr/test-data/doublet_stacked_bar_d.pdf b/tools/spacexr/test-data/doublet_stacked_bar_d.pdf
new file mode 100644
index 00000000000..8cc85271dbe
Binary files /dev/null and b/tools/spacexr/test-data/doublet_stacked_bar_d.pdf differ
diff --git a/tools/spacexr/test-data/metadata.tabular b/tools/spacexr/test-data/metadata.tabular
new file mode 100644
index 00000000000..0d115309316
--- /dev/null
+++ b/tools/spacexr/test-data/metadata.tabular
@@ -0,0 +1,476 @@
+barcode	annotation	nUMI
+Ib_M001_ATGCATGGTATCGTAC	type1	3377
+PFc_M001_GGTAGAGCAAAGCACG	type1	2691
+VI_F001_CCCGGAAGTTAAACCC	type1	1649
+AN1b_M006_GTCTACCAGCTTCGTA	type1	2354
+COPb_F002_CCGTGAGCATACGCAT	type1	4630
+III_F001_TTTGACTAGGATTTCC	type1	3334
+IXc_F002_AGGACGAGTCGTTCAA	type1	4835
+VIa_M006_CTTTCGGAGTCTTCCC	type1	3103
+AN2d_M006_ACCAAACTCACTGAAC	type1	3055
+SIMd_M002_CGATGCGCAGCAGAAC	type1	2895
+IV_M006_GTCCACTCATTGAGGG	type1	2477
+PRMf_M006_TGGGCGTCAATTAGGA	type1	3001
+VIIIb_F002_TGAGACTTCCAGCTCT	type1	5017
+AN1c_M002_AGGTTGTGTATTTCCT	type1	4003
+VIIb_M002_GTATTGGGTGGCTTAT	type1	2677
+I_M006_CTACGGGCATTAGGCT	type1	3866
+VIIIa_F002_AGAACCTGTATCGAGG	type1	3333
+Ib_M001_TCGAACAAGGGTCTTT	type1	2915
+AN2b_M002_TCCCATGGTCGCCTAG	type1	3811
+VIIIa_F002_CGTAGTACAAACTGCT	type1	3148
+Vl_M006_GGTGATTGTAGAATGT	type1	3011
+COPb_M002_CACTTCGAGATTGAGT	type1	4044
+PFa_M006_CCTTCAGTCGGTTAGT	type1	5039
+DECa_F002_AAGCCATCAGATACCT	type1	5110
+Ia_M001_GAGTGAGAGCACTAGG	type1	3632
+SIMa_M002_CATGGTAGTGGCACTC	type2	3244
+PRMc_M006_TAACTTCGTCCTTGTC	type2	3663
+SIMb_M002_AGGAGGTGTAGTATAG	type2	3954
+PFc_F002_GACCGTGCATCTATCT	type2	5917
+III_F001_TGACAGTAGACGCATG	type2	3651
+IXc_M003_CTAACCCGTTCAGTAC	type2	2337
+IIb_F001_GTTGTGAGTGACTAAA	type2	2616
+VIc_M002_TGGGAAGAGGCCGCTT	type2	5533
+Vb_M002_GAGTGAGTCGATTGGT	type2	4867
+SIMb_M006_TGATTTCAGTTTGCTG	type2	5654
+I_M006_TGTTACTAGATCACTC	type2	3724
+III_F001_CGATGGCGTTCCACAA	type2	2802
+I_M006_AACGGGACAGAACATA	type2	4378
+VIIIa_M001_TGAGACTCAATCGCGC	type2	4688
+IIb_M001_GTTTGGAGTGCATACT	type2	977
+VIc_M006_ACTATCTTCCAGCAAT	type2	9493
+VIIIa_M001_AGTGTTGGTGCTGATT	type2	4392
+IIa_M001_CAGATTGAGGCACAAC	type2	2107
+Ib_M001_ACTGCAAAGTCTTCCC	type2	4248
+PRMa_M006_CTTTCAACAGGTTCGC	type2	3683
+SIMa_M002_GACCAATAGCTTGTTG	type2	3673
+VIIIa_M001_CTGTAGATCCATTCAT	type2	3981
+SIM_F001_AACAAAGAGGTACAGC	type2	2562
+IXc_M006_TGATTTCCAAGTCCAT	type2	5825
+SIM_F001_TCGATTTAGAAGTCAT	type2	1868
+F_M006_CGAGTTACAGAAACCG	type3	8294
+F_M001_GTCTAGAAGAGTTCGG	type3	1228
+Xa_F001_TAAGTCGGTATACCTG	type3	6715
+DECb_M006_TTGGGCGGTGGTCTCG	type3	4729
+Va_M002_CTCCCTCAGGAACATT	type3	10097
+IXa_M003_TCATGCCAGACGAAGA	type3	2688
+VIb_M006_GAAACCTTCTTCTCAA	type3	5974
+Xb_F001_TCACGCTAGCCACCGT	type3	7834
+Ib_M001_TATTTCGAGGGTCTTT	type3	5397
+VIc_M006_ACTATCTAGGCTTTCA	type3	5000
+VIIb_F002_GATCCCTTCGTCAACA	type3	8013
+AN1b_M006_CACTGGGTCGCTTAAG	type3	2428
+IXa_M006_CCCGGAATCCTGTAAG	type3	7335
+Xa_F001_TGGTGATAGATTGGGC	type3	4267
+VIId_M002_TCTCACGAGAACAGGA	type3	4956
+IIIb_F001_GCAGCTGGTCAACGCC	type3	6594
+AN2a_F002_TGTCCTGTCCAGCAAT	type3	3497
+Ia_M001_ATTCCATCAGTTGAAA	type3	4198
+VIe_M002_AGGTCATGTTTCCATT	type3	8495
+SIMa_M002_CCTCCTCCAAGCTGTT	type3	5221
+Ib_M001_AGTGACTCAAGCTGCC	type3	5780
+IXc_F002_CCTCCTCTCGGACTTA	type3	14951
+X_M001_CTCCCTCAGTGTAGAT	type3	2128
+VIIb_M006_CCATAAGTCCACCCTA	type3	7417
+SIMd_M002_GTGATGTCATACAGGG	type3	2987
+I_F001_TCCCACAGTCTTCGAA	type4	7866
+PFa_M006_ATGTCCCTCGGTCTAA	type4	11217
+I_F001_ACCCTCACATGGACAG	type4	5304
+I_F001_CTCTCGATCATAAGGA	type4	5552
+PFa_M006_CAAAGAAGTTTACCAG	type4	16538
+PFa_M001_TCAATTCCAGACCGCT	type4	8223
+PFb_M001_CGGACACTCTCATGCC	type4	2953
+I_F001_ACGATGTCACCCTTGT	type4	6671
+Xa_M006_ATCACGACAAGCCATT	type4	7554
+I_F001_AGATCCAAGGAGCTGT	type4	4642
+I_F001_AACGGGAAGGTCTGGA	type4	4284
+PFa_M006_TAGACTGTCTTAGGAC	type4	18695
+I_F001_ACGGTTAAGCCGTCGT	type4	3394
+Xa_M006_ACTTCCGAGTGGATAT	type4	2520
+PFb_M006_TTCTAGTGTGCCGTAC	type4	10478
+PFa_M006_CGAGTGCGTTAGGCTT	type4	12828
+PFb_M001_CGAGTTAAGAGGTTAT	type4	11351
+PFb_M001_AGAACCTGTAGCTTGT	type4	11497
+PFa_M006_TGCTGAATCCTCTCGA	type4	14710
+Xa_M006_ACACGCGCAAATGCTC	type4	2420
+PFb_M006_GCTACCTAGCACGTCC	type4	12365
+PFa_M006_CGTTGGGCAGTCGAGA	type4	6759
+I_F001_AACCTTTGTGACCGAA	type4	4269
+IXc_M006_TGCGGGTGTGGTTCTA	type4	7073
+I_F001_CTGGCAGAGGGTTAGC	type4	3330
+Ib_M001_TCGACGGTCTCTTAAC	type5	2269
+PRMc_F002_TCATTTGCAGCTTCCT	type5	4495
+AN2a_M002_GCGGATCCAAGAGTAT	type5	2946
+IIb_M001_TCGCACTTCGTGGTAT	type5	3192
+VIIc_M002_AACGAAAGTAAGCTCT	type5	3686
+AN2b_M006_TATTGCTCACCGCTGA	type5	1303
+IIa_M001_GGGAAGTAGACTCTAC	type5	2843
+PRMc_M002_CCTTGTGGTCGATTAC	type5	3209
+AN2a_M002_CGAGTTATCCTACCAC	type5	4046
+IXa_M006_TGGTGATTCCAAGAGG	type5	5515
+PFc_M001_TACCCACCATGAATCC	type5	3020
+AN2b_F002_CCAATGAGTTAGTCGT	type5	2166
+AN2a_M006_GCAGGCTCACACGGAA	type5	1228
+AN2_M006_CCTCTAGGTTCTGACA	type5	7302
+IXb_M003_ATTCCTAGTAGCTGCC	type5	1786
+PFd_M001_GTCCCATGTCAGTCCG	type5	2044
+SIMd_M002_GACACGCGTATACCCA	type5	2446
+VId_M002_CATCCGTAGTTGAAAC	type5	4461
+PFc_M001_ACCAACAAGGCGTTAG	type5	2042
+PFc_M001_AATGGCTAGCATTTCG	type5	1409
+AN1b_M002_GAAGGACCAGTTTCGA	type5	3369
+VIIb_M006_CCGTGAGCACTGTCCT	type5	2961
+VIIc_M002_ACGTCCTCAAACGGCA	type5	3589
+CULb_M006_CCTAACCGTATGGTAA	type5	4012
+PFa_M006_CCTTTGGGTCTGTAAC	type5	3838
+PF_M006_CATGCAAGTCGCACAC	type6	11990
+IIb_F001_GCGATCGGTATGCGTT	type6	1912
+IXd_M006_GGAATGGAGAGAGTTT	type6	4350
+IXa_M003_GGGCCATAGTTTGGCT	type6	1282
+IXb_M006_CATCCGTGTCTCCCTA	type6	3277
+IXd_M006_TTAGTCTAGTAAACAC	type6	6367
+I_M006_ACAAGCTGTGTAGCAG	type6	3026
+IIb_F001_GGGACAAGTACGTGAG	type6	1895
+X_M001_GAGTTACCAGGACAGT	type6	1934
+IXa_M006_TGTAGACAGTTACGGG	type6	5282
+IXc_M003_TCCTAATTCGCCGTGA	type6	1263
+IIb_F001_TGGTAGTTCTATTTCG	type6	2670
+I_F001_ACGGTTAAGAGTTGCG	type6	1798
+IXb_M006_TTGCTGCGTCCACGCA	type6	5811
+I_M006_GACACGCGTGTCATTG	type6	3829
+Xa_M006_AGACACTCAGGAATAT	type6	8426
+IXa_M006_GCGGAAAAGATCCTAC	type6	4167
+I_F001_GCAACCGAGTGAGGTC	type6	3108
+IXa_M006_CCCAACTTCGAGAAAT	type6	5724
+IXb_M006_TGTGCGGCATCAACCA	type6	4671
+PFa_M006_AGACAAAGTCATTCCC	type6	4716
+Xa_M006_ATTTCTGGTCGGAAAC	type6	2445
+I_M006_TTATTGCGTCGAATGG	type6	7814
+IIa_M001_CCTACGTAGGGATCTG	type6	2883
+Xa_M006_CGATGCGAGCGACTAG	type6	1891
+PRMa_M006_CAATGACAGACCACGA	type7	7414
+PF_M006_CCGCAAGAGTAAAGCT	type7	3235
+COPb_M002_ATCGATGGTAACTGCT	type7	10821
+IV_M006_ATTTACCAGGGCGAAG	type7	1398
+PRMb_M002_TATATCCAGGTCACTT	type7	8238
+AN2b_M002_ACGTAGTCAGGCACTC	type7	7790
+AN2a_M002_TCTGTCGTCTCGGTCT	type7	6533
+PRMc_M006_GATCATGTCGCTTTAT	type7	2113
+PFa_M001_GCCAACGCATGTACGT	type7	5487
+AN1a_F002_ATATCCTCATGCGGTC	type7	5692
+AN2e_M006_TAGCACAGTAGGATAT	type7	3976
+AN1c_F002_GGAGAACTCACCTTAT	type7	19360
+PRMe_M002_TGGTACACAATGCTCA	type7	790
+PFd_M001_AGGTTACTCTCTGCTG	type7	4398
+VIIa_M006_TACCGAAAGCCTCTCT	type7	3276
+PFb_F002_GCTGCAGCACTCGATA	type7	1765
+CULb_M006_TCGCACTGTTCCCACT	type7	3039
+VIIb_M006_GCGGATCAGTGCAACG	type7	5772
+AN2d_M006_ACAAAGATCGCTTAAG	type7	3883
+PF_M006_GAAGGGTCACTTGGCG	type7	10379
+PF_M006_TTACCGCCACCTGCGA	type7	2668
+PRMa_M002_ACGATCATCTTGCAGA	type7	5532
+AN2a_M002_CAAGGGATCGTCCTCA	type7	6038
+PRMe_M002_GAGGCAAAGAGTGAAG	type7	608
+SIMd_M002_GTTCGCTGTACTGAGG	type7	2033
+Ib_M001_ATCCTATGTACCCAGC	type8	4289
+III_F001_CGCCATTGTCCAAATC	type8	5308
+Xb_F001_TGGGAGAGTTGTTGTG	type8	6562
+SIMa_M002_ATCGTGACAGCTCGGT	type8	4280
+IIb_M001_AGGTTGTCATGTTACG	type8	4130
+VId_M002_CCGATCTAGGAAAGTG	type8	5441
+Xb_F001_TCATGAGAGAAGTCTA	type8	5340
+SIMb_M006_AAAGTGATCTGGTTGA	type8	7872
+AN1b_F002_ATTCCCGGTGCGGTAA	type8	7570
+COPa_F002_CCGATGGAGTTGCCCG	type8	10235
+PRMb_M006_GATGGAGGTTGGCCTG	type8	4536
+PRMd_M006_ACAAGCTAGTATGACA	type8	5527
+VI_F001_AGTGCCGGTCGCATTA	type8	2792
+III_F001_TGACCCTTCGAACTCA	type8	6187
+I_M006_CAGCACGTCACGATAC	type8	6014
+III_F001_TGCAGGCCAAATCGTC	type8	7229
+AN2_M006_AGAGAATGTTAGTCGT	type8	17525
+III_F001_GAGTTACGTACACGCC	type8	6143
+AN2e_M006_GCGGATCTCCTATTTG	type8	4847
+PFc_M001_GACCAATCAAGCGATG	type8	7400
+AN1b_M006_GCGGATCCATCACCAA	type8	5209
+IIa_M001_ACCGTTCAGCAACCAG	type8	4455
+SIMa_M002_CAGTTCCGTTTCACTT	type8	11800
+IIb_M001_GAGTTACTCACGGAGA	type8	3695
+IIb_M001_AACCTTTCATACCATG	type8	2914
+SIM_F001_CATGCGGAGGGTGAGG	type9	6267
+IV_M006_GTGACGCTCTAGCAAC	type9	5225
+IXa_F002_TAGGTTGTCTGGGAGA	type9	10477
+PFc_M001_GATCGTAGTCCGATCG	type9	14199
+IXc_M003_GCGGATCGTCCCGTGA	type9	1988
+AN1c_F002_TTCCTTCAGTTCCAGT	type9	13351
+PFc_F002_TCACTATGTAGTCTGT	type9	23593
+PRMb_F002_CAGTTAGGTTAGTCGT	type9	18073
+VIIIa_M001_GTAACACGTTAGAGTA	type9	15911
+AN1c_M002_TCAAGCATCTGCGGCA	type9	22606
+PRMc_F002_ACTACGATCACCTCGT	type9	13933
+IXa_M003_TAATTCCAGGCAGGTT	type9	7595
+IIIa_M001_TGTTCATGTCGCGTCA	type9	7095
+IIb_F001_CTCTCAGCACTCCTGT	type9	9908
+DECa_F002_GCGAGAAGTCTAACTG	type9	22504
+PFc_M001_AGGAGGTCACTGGCCA	type9	13646
+Xb_F001_GACTCAAAGTGCACAG	type9	7220
+Vl_M006_GTTACAGAGTGGTTCT	type9	9990
+VIb_M002_ACTGATGGTGTGCTTA	type9	14773
+PFa_F002_TGGTAGTAGCATCTTG	type9	28127
+PFb_M001_TAACTTCGTCTGCAAT	type9	13397
+PRMc_M006_TGTTCCGTCCTTTGAT	type9	8678
+VIc_M006_ACTGATGCAGGAACCA	type9	7363
+IIb_F001_AGACCATAGCGCTTCG	type9	11583
+AN2b_M006_TCGCTCAGTGGCACTC	type9	14117
+VIIIb_M001_TATCTTGCACCTGTCT	type10	3341
+PFd_M001_AGGACGAGTGAGTAAT	type10	2308
+Ia_M001_GCAGCTGCACAAGCCC	type10	7076
+SIMc_M002_CTCCAACAGAGCCCAA	type10	3154
+VIc_M002_CCTCTCCTCCTACCGT	type10	5699
+DECa_F002_TTCGATTAGGTTATAG	type10	3533
+VIIb_M002_GACGTTACAAAGGCTG	type10	1843
+SIMa_M002_ATAGACCCATAGGTTC	type10	2607
+VI_F001_CCGGACAAGAGTTGCG	type10	1188
+IIIa_M001_GTAAGTCGTATCGTGT	type10	1002
+AN1a_F002_CATCAAGAGCCGTTAT	type10	3262
+VI_F001_TTGAGTGCACAAGTTC	type10	1140
+PFa_M001_AAGACAACAATACCTG	type10	1412
+AN1c_M002_CATCGTCGTGACCGTC	type10	2382
+VIc_M002_CTGTATTTCTCGACGG	type10	3822
+III_F001_GCGTGCACACTCAGAT	type10	1729
+VIIa_F002_CCGATGGGTGAGCTCC	type10	1916
+IIa_F001_GACTATGAGGTCGTAG	type10	2586
+CULb_M006_AGGACTTGTCGAGCTC	type10	3432
+PRMb_M006_GCTTGGGCATTGCTGA	type10	1971
+COPc_M002_TGCTCGTCATCGTGCG	type10	1739
+Xa_M006_TTGACCCAGTAAAGCT	type10	3080
+IIb_F001_ACCCTTGTCCTAGAGT	type10	3488
+DECc_M006_GAGTCATCAAGTGGAC	type10	3602
+PRMe_M006_CTCAGGGCACGCTGCA	type10	2320
+IIa_M001_TGTGTGATCTCGTCGT	type11	5840
+IV_M006_AGTCAACAGAAGCGCT	type11	7000
+PRMa_F002_GTTATGGTCATACGAC	type11	17671
+VIa_M002_ATACCTTAGTCTAACC	type11	8077
+Xa_F001_CATGCGGGTTCTCAGA	type11	14366
+AN2b_M002_GGGCTCAAGCCTGAAG	type11	10223
+AN1a_F002_ACTTCGCAGTTACTCG	type11	3865
+PFb_M001_ACCTGTCAGAAATTGC	type11	10086
+PFb_M001_CTGTCGTGTGACACAG	type11	10589
+VIIb_M006_CAAAGAATCGCGATCG	type11	11803
+IIIb_F001_TTATTGCAGAACAGGA	type11	9226
+VIIb_F002_GCCGTGACATTATGCG	type11	7116
+DECa_M006_CAGATCATCGAGTTGT	type11	17287
+PFa_F002_AACAGGGCAATACCCA	type11	15984
+X_M001_CCCGAAGCAAGCGGAT	type11	4542
+VIc_M006_GTCATGAAGGTATCTC	type11	8015
+Ia_M001_TTACGTTCACCAGTAT	type11	7607
+IXa_F002_TGAGACTTCTAAGAAG	type11	10697
+VIIb_M002_ATTCCCGCAGTCGGAA	type11	6344
+VIIb_M002_CTCCATGAGATGCAGC	type11	9560
+Xb_F001_CGATGCGTCCACCCTA	type11	6314
+COPa_F002_TTGCCTGGTCGTGTTA	type11	9658
+Fc_M006_TCGCACTTCGCTGCGA	type11	6645
+VIIIb_M001_CAGCAATCAAATCGGG	type11	6590
+AN2b_F002_GGGCTCAGTAGGTACG	type11	11877
+VIc_M002_AGGAAATGTCTCACAA	type12	2075
+AN2b_F002_TCATGCCCATGGCACC	type12	2480
+SIM_F001_CAGTTCCAGAGGTCAC	type12	2022
+SIMa_M002_TTCAATCTCGAAACAA	type12	2681
+PRMe_M002_CTGCCATTCCGCGGAT	type12	2512
+SIMa_M006_CCGGGTACAGGGACTA	type12	1990
+DECc_M006_GTAGGAGTCAACCCGG	type12	2423
+PRMb_M002_TCCATGCTCTACAGGT	type12	2787
+PRMd_M002_CCAATTTGTATCAGCT	type12	938
+PFd_M001_GAATCACCAGGCACAA	type12	2528
+AN2b_F002_CCTCCTCTCGGAATGG	type12	2183
+AN2b_F002_GTGCACGTCAGAGCGA	type12	1958
+VIIIc_F002_CGTGATATCTCTGGTC	type12	2623
+VIb_M002_ATCATTCAGTATCTGC	type12	3427
+PRMa_M002_TGGGCGTTCGATCCAA	type12	1414
+PF_M006_CAGATCATCGCTAAAC	type12	3465
+VIe_M002_GCAGCCATCGCAGTCG	type12	4234
+VIIa_M006_AATTCCTAGTAACGTA	type12	2524
+IXc_M003_AGAGCCCTCATTGCGA	type12	790
+PFb_F002_CACGAATGTGTAACGG	type12	3079
+VIa_M002_CGTAAGTCATGGTACT	type12	2348
+COPa_M002_GGTGTTAAGCTGTTAC	type12	2427
+Ia_M001_ACTTTCAGTATTCCGA	type12	1664
+I_M006_TCACACCAGTGTAGAT	type12	2381
+VI_F001_TAATTCCTCGTAGCCG	type12	1614
+VIIIb_F002_ACATTTCCATTGGATC	type13	1909
+SIM_F001_AGCTCAAGTCAATGGG	type13	988
+Vc_M002_TAGTGCACATGGAGAC	type13	2601
+AN2c_M006_TTTGGAGTCATGCGGC	type13	1655
+Vc_M002_CTACCCAGTGTCTAAC	type13	3586
+Vb_M002_GATTCTTCATTCACCC	type13	2945
+Va_M002_GTTTGGAGTTGCCATA	type13	2417
+Vb_M002_TCTACCGTCAAGAATG	type13	3499
+VIb_M006_CCTCCAAGTGAACCGA	type13	2049
+Xa_F001_CCACCATTCCCAGCGA	type13	2064
+PFb_F002_TGACAGTAGCCTCTCT	type13	3096
+VIIId_F002_GAGTGAGCAACACTAC	type13	2049
+VIIIb_M001_GTTTACTCACTGCTTC	type13	2406
+AN2c_M002_TATATCCTCAGTCTTT	type13	2729
+PFb_M006_TAGCACATCTTCTGTA	type13	2986
+AN2a_M006_AGTCAACTCATCACCC	type13	1552
+IIb_F001_GTAGGAGAGGCGACAT	type13	1342
+DECb_M006_GTGAGCCAGGAACATT	type13	2326
+VIIIb_M001_CGTAGTACAAATGCGG	type13	1552
+AN2a_M002_AGGATAATCACTAGCA	type13	2067
+F_M001_TCTCCGAAGCAGCAGT	type13	817
+VIIIb_F002_TCATTACGTCGAAACG	type13	1431
+Fa_M006_AGCGATTCAAATACAG	type13	2779
+COP_M006_AAGTGAAGTTGTGGCC	type13	1803
+AN2c_M006_AACAGGGAGTGCCAGA	type13	1431
+IXa_M003_TGGTTAGCAGCTTTCC	type14	2261
+PF_M006_CCTCACATCGGACCAC	type14	5539
+Vc_M002_CTCCACAAGCGGCTCT	type14	11180
+AN1b_M006_TGTCCCACATCGGCCA	type14	3529
+SIM_F001_TGGTAGTTCGCGTTTC	type14	3056
+IXb_F002_CACCGTTGTGAGTGAC	type14	6485
+VIIIc_F002_CTCTCGAAGAGTGTGC	type14	5966
+AN2c_M002_CTGCTCAGTCGATTTG	type14	6341
+AN2b_M002_TTCATGTGTTACAGCT	type14	6897
+VIId_M002_GGTGAAGCAAGGTACG	type14	3834
+VIIIc_F002_CCACCATTCACCTGTC	type14	6866
+IV_M006_CCTCACACAAAGAGTT	type14	3856
+VIc_M002_AGGATCTAGGTATTGA	type14	7943
+AN2a_M006_TCGTAGAAGCTCTGTA	type14	2517
+AN2a_M006_AGATCCATCAATGTCG	type14	5816
+IIa_F001_GTTAGACCATCTATCT	type14	6914
+COPa_F002_CTCCACAGTCTATGAC	type14	11857
+IXa_M003_AGGCCACGTCGCGTCA	type14	2003
+VIa_M006_CACTTCGAGAAACTAC	type14	7318
+IXa_M003_GTAGGAGCAATAGTCC	type14	2231
+PRMe_M006_AGTCTCCAGAGAGTGA	type14	4287
+PRMb_M002_CTACAGAGTATCGTAC	type14	5187
+VI_F001_AACAAAGAGGCTGTAG	type14	2795
+IIIb_F001_CTGCTCAAGCCTAACT	type14	3601
+IIIb_F001_GTGGAAGCAGCATTGT	type14	3051
+F_F001_TGTGTGAAGCCACAAG	type15	4957
+AN2a_M002_TGGTAGTGTGGATCGA	type15	5236
+I_F001_TTCTTGATCCCGATCT	type15	2703
+AN1a_M006_GTGGGAAGTACGACAG	type15	3450
+PFc_F002_AACCATGGTCATGCAT	type15	9573
+VIIIa_F002_CGTTCTGTCGATACTG	type15	7785
+VIb_M006_TCTGCCAAGGACAGTC	type15	3808
+VIb_M006_ATTCTTGCAACTGGTT	type15	3440
+VIb_M006_GGATCTAAGGATTCCT	type15	3720
+AN1b_M002_TACCGAATCAGCGTCG	type15	4179
+II_M006_AGTGACTGTCAGGAGT	type15	8006
+VI_F001_AACACACGTGACTAAA	type15	2688
+IIa_M001_AGGGTGATCTATCGGA	type15	3410
+VIIId_F002_TGTTACTAGCCTCTTC	type15	8110
+IXc_M003_AGACACTTCCCAGCGA	type15	3206
+AN2c_F002_CCGTGAGAGGCACCAA	type15	6956
+VIc_M002_TCTATCATCCATAGGT	type15	4358
+VIb_M002_ACCATTTAGACTTCCA	type15	6529
+SIM_F001_TTCGGTCCATGTGTCA	type15	2370
+VIb_M006_CTCATTATCAGCCCAG	type15	5334
+IXb_M003_ACACTGATCATGACAC	type15	4486
+IIb_M001_TTGGGCGCACAATTCG	type15	4673
+F_M006_GGAGCAAAGCTAATCC	type15	9530
+IIIa_M001_TGCGGGTCACACACTA	type15	2934
+Vb_M002_GTCATCCCAGCTGTTA	type15	9395
+PF_M006_CCATAAGAGATCCTAC	type16	6432
+AN1c_M002_GCGGAAATCACTCGAA	type16	4042
+PF_M006_AGACCATGTATGGTAA	type16	4645
+Fc_M006_CCTACGTTCTCGAGTA	type16	5395
+PRMc_F002_TGGAACTCAAAGCAAT	type16	2043
+VIIIc_F002_GGAGCAATCTACCCAC	type16	5260
+AN2c_F002_TTACAGGTCGCCAGTG	type16	4236
+PRMa_M006_AACCAACGTAGCGTTT	type16	3033
+AN2c_F002_GGGTGAAGTCATCACA	type16	3600
+AN2c_M006_TTAGGGTTCTAACACG	type16	3417
+PF_M006_GTCGAATGTAGGCTCC	type16	3754
+Vc_M002_GCCTGTTGTCTGGTTA	type16	4172
+Ib_M001_GTGATGTGTCGGTGTC	type16	2209
+PRMa_M006_TACAGGTCATCGTCCT	type16	2875
+AN2b_F002_TCGACGGCAAGCTGTT	type16	4202
+VIc_M006_CGGAATTCAGAGTTGG	type16	2449
+PFb_M006_TGTTGAGAGCGCATCC	type16	2821
+Ia_M001_GCCAGGTAGCAGTAAT	type16	2732
+F_M006_TCGGTCTTCTTGCAGA	type16	7461
+AN1b_F002_TCATTACAGACTTCGT	type16	4418
+Vb_M002_ACGATGTTCTGGGTCG	type16	3438
+AN2e_M006_GCATCGGAGCGCTGCT	type16	3011
+IXb_M003_CCATCACCATACAGCT	type16	3428
+IXb_M003_CTCCATGGTGGATTTC	type16	1457
+IXa_M003_AGGGTCCTCTTTGCGC	type16	1434
+VIIb_M006_GTAGAAAGTCCGTTTC	type18	10291
+IXc_M006_GACCTTCTCATTGGTG	type18	13566
+PRMe_M002_GCTTCACAGGGTACGT	type18	4354
+IXc_F002_ACGGAAGGTACAAGTA	type18	7222
+PRMb_M002_CTATAGGCACAAAGTA	type18	3785
+VIIb_M006_CCACCATGTCCTTAAG	type18	8356
+PRMa_M006_ACGTCCTAGCCTATTG	type18	4221
+VIIb_M002_ACGGGTCCACCGCTGA	type18	3644
+AN2a_M002_TATACCTGTTGGAGAC	type18	5644
+IIa_M001_TGCAGATTCTCATTGT	type18	7566
+PRMf_M006_TAACACGTCACCTTAT	type18	8442
+IXc_M006_TGTTCATCACTGGCCA	type18	6765
+PFb_M001_AGGTTACCAACCAATC	type18	5212
+VIIIb_F002_TTTCAGTTCCATCCGT	type18	5487
+AN2a_F002_TAGGGTTCAATGAGCG	type18	3345
+AN2_M006_AGAGCCCCAACTCGAT	type18	6083
+AN2e_M006_TTGCATTAGACTCGAG	type18	4334
+PRMf_M006_TGTCCACTCGGTGCAC	type18	5606
+AN1b_M006_AACCCAAGTTGGATCT	type18	3278
+AN1c_F002_CTGAGGCGTCGAGCTC	type18	3338
+II_M006_GTTTGGAAGTGCGACA	type18	6788
+PFb_F002_CAAGAGGAGTTCACTG	type18	8098
+PF_M006_ATGCCTCAGGAAGTAG	type18	3685
+VIb_M002_TTCTCTCCATCCTCAC	type18	14193
+X_M001_ACGATCATCAAGTTGC	type18	3705
+VIIId_F002_AGATCCAAGTTAGAAC	type18	33995
+IIa_F001_GCATGATGTATAGCTC	type18	33468
+PFc_M001_CATACAGAGGCAGGGA	type18	15197
+PF_M006_TACGTCCTCTGTTCAT	type18	34409
+AN1_M006_CCGATCTTCGTAGAGG	type18	14458
+AN2d_M006_GCCATTCCATGGGAAC	type18	27917
+F_F001_CCCTCTCCATACCAGT	type18	37032
+AN1c_F002_GAGTTACAGTATGAAC	type18	31618
+IXb_M006_TCAGTGACAAGGTTGG	type18	32956
+Xb_F001_TGGATGTCAGACAATA	type18	19533
+VIa_M006_GACCCTTGTACCGCGT	type18	17635
+PRMa_F002_CTGGCAGGTTTGTTCT	type18	36960
+PF_M006_CATACCCGTACTGAGG	type18	33479
+Ib_M001_ATGGTTGTCGGTCGAC	type18	16796
+SIM_F001_ATATCCTAGTTGGAGC	type18	11336
+PRMa_F002_GGTAATCGTCTACTGA	type18	41936
+AN2e_M006_CTCAAGACACAACGCC	type18	36102
+VId_M002_AACCTGATCGGTGAAG	type18	32496
+AN2c_M002_TGTACAGTCTTAGTTC	type18	32071
+AN1a_M002_GAATCGTGTGCTATTG	type18	30148
+DECc_M006_ATCACGAGTAGCGAGT	type18	27767
+AN2e_M006_GACTCAAGTTTGTGGT	type18	33244
+IV_M006_CTGAGGCGTTCCAAAC	type18	11782
+Ib_M001_GACAGCCTCCGTTGAA	type18	15025
+SIMc_M002_AAGTGAATCAGAACCT	type18	21752
+IXc_M003_GCAACCGAGATGCTAA	type19	2834
+Xa_F001_TACTGCCGTCATAGTC	type19	5559
+Xa_F001_TCGAAGTCACTTGTCC	type19	4834
+Xb_F001_CATGCCTCAGACGCTC	type19	6097
+IXa_F002_TCATACTGTCACTGAT	type19	7768
+IXc_M003_CGGGCATGTTCGGTTA	type19	2045
+VIIa_M006_AGGTCTAAGAGCATAT	type19	5779
+PFc_M001_ATTACCTAGTTACTCG	type19	3551
+VIIb_F002_TTTGGTTAGGTTGCCC	type19	5577
+F_F001_TATATCCTCGTGCGAC	type19	4151
+IXa_M003_AAGTTCGGTGATACCT	type19	2938
+PFb_F002_GAGTCATTCGCGTAGC	type19	9732
+PFa_F002_AGGGCCTAGGAACGTC	type19	7183
+AN2b_M002_AACCACATCCACCTGT	type19	2814
+Xb_F001_AGGGTCCTCATTTCCA	type19	5600
+PRMb_M006_GAGTCATTCGGTCTAA	type19	5106
+PFd_M001_GTAGAGGAGGTTAAAC	type19	3763
+IIa_F001_CGTCAAAAGAATCCCT	type19	4485
+AN2c_F002_TAAGTCGCAACCAGAG	type19	6783
+VIIId_F002_GGTAGAGCACGCACCA	type19	4829
+I_F001_TCGGGCACATGGAGAC	type19	3125
+I_F001_TGACCCTGTAGACGGT	type19	3131
+Fc_M006_GTTGTGACATCCGAGC	type19	4633
+Ib_M001_GACCCTTTCATACGGT	type19	4713
+I_F001_GTAGAAAGTTCCACAA	type19	2650
diff --git a/tools/spacexr/test-data/myRCTD_merfish.rds b/tools/spacexr/test-data/myRCTD_merfish.rds
new file mode 100644
index 00000000000..0ea82e3bf8a
Binary files /dev/null and b/tools/spacexr/test-data/myRCTD_merfish.rds differ
diff --git a/tools/spacexr/test-data/nUMI_plot.pdf b/tools/spacexr/test-data/nUMI_plot.pdf
new file mode 100644
index 00000000000..07dd8269c73
Binary files /dev/null and b/tools/spacexr/test-data/nUMI_plot.pdf differ
diff --git a/tools/spacexr/test-data/rds_doublet.rds b/tools/spacexr/test-data/rds_doublet.rds
new file mode 100644
index 00000000000..0f6c1c7229a
Binary files /dev/null and b/tools/spacexr/test-data/rds_doublet.rds differ
diff --git a/tools/spacexr/test-data/rds_full.rds b/tools/spacexr/test-data/rds_full.rds
new file mode 100644
index 00000000000..7cd453c06dd
Binary files /dev/null and b/tools/spacexr/test-data/rds_full.rds differ
diff --git a/tools/spacexr/test-data/rds_multi.rds b/tools/spacexr/test-data/rds_multi.rds
new file mode 100644
index 00000000000..cfe94e054b2
Binary files /dev/null and b/tools/spacexr/test-data/rds_multi.rds differ
diff --git a/tools/spacexr/test-data/sc_count.tabular b/tools/spacexr/test-data/sc_count.tabular
new file mode 100644
index 00000000000..92105988270
--- /dev/null
+++ b/tools/spacexr/test-data/sc_count.tabular
@@ -0,0 +1,385 @@
+Ib_M001_ATGCATGGTATCGTAC	PFc_M001_GGTAGAGCAAAGCACG	VI_F001_CCCGGAAGTTAAACCC	AN1b_M006_GTCTACCAGCTTCGTA	COPb_F002_CCGTGAGCATACGCAT	III_F001_TTTGACTAGGATTTCC	IXc_F002_AGGACGAGTCGTTCAA	VIa_M006_CTTTCGGAGTCTTCCC	AN2d_M006_ACCAAACTCACTGAAC	SIMd_M002_CGATGCGCAGCAGAAC	IV_M006_GTCCACTCATTGAGGG	PRMf_M006_TGGGCGTCAATTAGGA	VIIIb_F002_TGAGACTTCCAGCTCT	AN1c_M002_AGGTTGTGTATTTCCT	VIIb_M002_GTATTGGGTGGCTTAT	I_M006_CTACGGGCATTAGGCT	VIIIa_F002_AGAACCTGTATCGAGG	Ib_M001_TCGAACAAGGGTCTTT	AN2b_M002_TCCCATGGTCGCCTAG	VIIIa_F002_CGTAGTACAAACTGCT	Vl_M006_GGTGATTGTAGAATGT	COPb_M002_CACTTCGAGATTGAGT	PFa_M006_CCTTCAGTCGGTTAGT	DECa_F002_AAGCCATCAGATACCT	Ia_M001_GAGTGAGAGCACTAGG	SIMa_M002_CATGGTAGTGGCACTC	PRMc_M006_TAACTTCGTCCTTGTC	SIMb_M002_AGGAGGTGTAGTATAG	PFc_F002_GACCGTGCATCTATCT	III_F001_TGACAGTAGACGCATG	IXc_M003_CTAACCCGTTCAGTAC	IIb_F001_GTTGTGAGTGACTAAA	VIc_M002_TGGGAAGAGGCCGCTT	Vb_M002_GAGTGAGTCGATTGGT	SIMb_M006_TGATTTCAGTTTGCTG	I_M006_TGTTACTAGATCACTC	III_F001_CGATGGCGTTCCACAA	I_M006_AACGGGACAGAACATA	VIIIa_M001_TGAGACTCAATCGCGC	IIb_M001_GTTTGGAGTGCATACT	VIc_M006_ACTATCTTCCAGCAAT	VIIIa_M001_AGTGTTGGTGCTGATT	IIa_M001_CAGATTGAGGCACAAC	Ib_M001_ACTGCAAAGTCTTCCC	PRMa_M006_CTTTCAACAGGTTCGC	SIMa_M002_GACCAATAGCTTGTTG	VIIIa_M001_CTGTAGATCCATTCAT	SIM_F001_AACAAAGAGGTACAGC	IXc_M006_TGATTTCCAAGTCCAT	SIM_F001_TCGATTTAGAAGTCAT	F_M006_CGAGTTACAGAAACCG	F_M001_GTCTAGAAGAGTTCGG	Xa_F001_TAAGTCGGTATACCTG	DECb_M006_TTGGGCGGTGGTCTCG	Va_M002_CTCCCTCAGGAACATT	IXa_M003_TCATGCCAGACGAAGA	VIb_M006_GAAACCTTCTTCTCAA	Xb_F001_TCACGCTAGCCACCGT	Ib_M001_TATTTCGAGGGTCTTT	VIc_M006_ACTATCTAGGCTTTCA	VIIb_F002_GATCCCTTCGTCAACA	AN1b_M006_CACTGGGTCGCTTAAG	IXa_M006_CCCGGAATCCTGTAAG	Xa_F001_TGGTGATAGATTGGGC	VIId_M002_TCTCACGAGAACAGGA	IIIb_F001_GCAGCTGGTCAACGCC	AN2a_F002_TGTCCTGTCCAGCAAT	Ia_M001_ATTCCATCAGTTGAAA	VIe_M002_AGGTCATGTTTCCATT	SIMa_M002_CCTCCTCCAAGCTGTT	Ib_M001_AGTGACTCAAGCTGCC	IXc_F002_CCTCCTCTCGGACTTA	X_M001_CTCCCTCAGTGTAGAT	VIIb_M006_CCATAAGTCCACCCTA	SIMd_M002_GTGATGTCATACAGGG	I_F001_TCCCACAGTCTTCGAA	PFa_M006_ATGTCCCTCGGTCTAA	I_F001_ACCCTCACATGGACAG	I_F001_CTCTCGATCATAAGGA	PFa_M006_CAAAGAAGTTTACCAG	PFa_M001_TCAATTCCAGACCGCT	PFb_M001_CGGACACTCTCATGCC	I_F001_ACGATGTCACCCTTGT	Xa_M006_ATCACGACAAGCCATT	I_F001_AGATCCAAGGAGCTGT	I_F001_AACGGGAAGGTCTGGA	PFa_M006_TAGACTGTCTTAGGAC	I_F001_ACGGTTAAGCCGTCGT	Xa_M006_ACTTCCGAGTGGATAT	PFb_M006_TTCTAGTGTGCCGTAC	PFa_M006_CGAGTGCGTTAGGCTT	PFb_M001_CGAGTTAAGAGGTTAT	PFb_M001_AGAACCTGTAGCTTGT	PFa_M006_TGCTGAATCCTCTCGA	Xa_M006_ACACGCGCAAATGCTC	PFb_M006_GCTACCTAGCACGTCC	PFa_M006_CGTTGGGCAGTCGAGA	I_F001_AACCTTTGTGACCGAA	IXc_M006_TGCGGGTGTGGTTCTA	I_F001_CTGGCAGAGGGTTAGC	Ib_M001_TCGACGGTCTCTTAAC	PRMc_F002_TCATTTGCAGCTTCCT	AN2a_M002_GCGGATCCAAGAGTAT	IIb_M001_TCGCACTTCGTGGTAT	VIIc_M002_AACGAAAGTAAGCTCT	AN2b_M006_TATTGCTCACCGCTGA	IIa_M001_GGGAAGTAGACTCTAC	PRMc_M002_CCTTGTGGTCGATTAC	AN2a_M002_CGAGTTATCCTACCAC	IXa_M006_TGGTGATTCCAAGAGG	PFc_M001_TACCCACCATGAATCC	AN2b_F002_CCAATGAGTTAGTCGT	AN2a_M006_GCAGGCTCACACGGAA	AN2_M006_CCTCTAGGTTCTGACA	IXb_M003_ATTCCTAGTAGCTGCC	PFd_M001_GTCCCATGTCAGTCCG	SIMd_M002_GACACGCGTATACCCA	VId_M002_CATCCGTAGTTGAAAC	PFc_M001_ACCAACAAGGCGTTAG	PFc_M001_AATGGCTAGCATTTCG	AN1b_M002_GAAGGACCAGTTTCGA	VIIb_M006_CCGTGAGCACTGTCCT	VIIc_M002_ACGTCCTCAAACGGCA	CULb_M006_CCTAACCGTATGGTAA	PFa_M006_CCTTTGGGTCTGTAAC	PF_M006_CATGCAAGTCGCACAC	IIb_F001_GCGATCGGTATGCGTT	IXd_M006_GGAATGGAGAGAGTTT	IXa_M003_GGGCCATAGTTTGGCT	IXb_M006_CATCCGTGTCTCCCTA	IXd_M006_TTAGTCTAGTAAACAC	I_M006_ACAAGCTGTGTAGCAG	IIb_F001_GGGACAAGTACGTGAG	X_M001_GAGTTACCAGGACAGT	IXa_M006_TGTAGACAGTTACGGG	IXc_M003_TCCTAATTCGCCGTGA	IIb_F001_TGGTAGTTCTATTTCG	I_F001_ACGGTTAAGAGTTGCG	IXb_M006_TTGCTGCGTCCACGCA	I_M006_GACACGCGTGTCATTG	Xa_M006_AGACACTCAGGAATAT	IXa_M006_GCGGAAAAGATCCTAC	I_F001_GCAACCGAGTGAGGTC	IXa_M006_CCCAACTTCGAGAAAT	IXb_M006_TGTGCGGCATCAACCA	PFa_M006_AGACAAAGTCATTCCC	Xa_M006_ATTTCTGGTCGGAAAC	I_M006_TTATTGCGTCGAATGG	IIa_M001_CCTACGTAGGGATCTG	Xa_M006_CGATGCGAGCGACTAG	PRMa_M006_CAATGACAGACCACGA	PF_M006_CCGCAAGAGTAAAGCT	COPb_M002_ATCGATGGTAACTGCT	IV_M006_ATTTACCAGGGCGAAG	PRMb_M002_TATATCCAGGTCACTT	AN2b_M002_ACGTAGTCAGGCACTC	AN2a_M002_TCTGTCGTCTCGGTCT	PRMc_M006_GATCATGTCGCTTTAT	PFa_M001_GCCAACGCATGTACGT	AN1a_F002_ATATCCTCATGCGGTC	AN2e_M006_TAGCACAGTAGGATAT	AN1c_F002_GGAGAACTCACCTTAT	PRMe_M002_TGGTACACAATGCTCA	PFd_M001_AGGTTACTCTCTGCTG	VIIa_M006_TACCGAAAGCCTCTCT	PFb_F002_GCTGCAGCACTCGATA	CULb_M006_TCGCACTGTTCCCACT	VIIb_M006_GCGGATCAGTGCAACG	AN2d_M006_ACAAAGATCGCTTAAG	PF_M006_GAAGGGTCACTTGGCG	PF_M006_TTACCGCCACCTGCGA	PRMa_M002_ACGATCATCTTGCAGA	AN2a_M002_CAAGGGATCGTCCTCA	PRMe_M002_GAGGCAAAGAGTGAAG	SIMd_M002_GTTCGCTGTACTGAGG	Ib_M001_ATCCTATGTACCCAGC	III_F001_CGCCATTGTCCAAATC	Xb_F001_TGGGAGAGTTGTTGTG	SIMa_M002_ATCGTGACAGCTCGGT	IIb_M001_AGGTTGTCATGTTACG	VId_M002_CCGATCTAGGAAAGTG	Xb_F001_TCATGAGAGAAGTCTA	SIMb_M006_AAAGTGATCTGGTTGA	AN1b_F002_ATTCCCGGTGCGGTAA	COPa_F002_CCGATGGAGTTGCCCG	PRMb_M006_GATGGAGGTTGGCCTG	PRMd_M006_ACAAGCTAGTATGACA	VI_F001_AGTGCCGGTCGCATTA	III_F001_TGACCCTTCGAACTCA	I_M006_CAGCACGTCACGATAC	III_F001_TGCAGGCCAAATCGTC	AN2_M006_AGAGAATGTTAGTCGT	III_F001_GAGTTACGTACACGCC	AN2e_M006_GCGGATCTCCTATTTG	PFc_M001_GACCAATCAAGCGATG	AN1b_M006_GCGGATCCATCACCAA	IIa_M001_ACCGTTCAGCAACCAG	SIMa_M002_CAGTTCCGTTTCACTT	IIb_M001_GAGTTACTCACGGAGA	IIb_M001_AACCTTTCATACCATG	SIM_F001_CATGCGGAGGGTGAGG	IV_M006_GTGACGCTCTAGCAAC	IXa_F002_TAGGTTGTCTGGGAGA	PFc_M001_GATCGTAGTCCGATCG	IXc_M003_GCGGATCGTCCCGTGA	AN1c_F002_TTCCTTCAGTTCCAGT	PFc_F002_TCACTATGTAGTCTGT	PRMb_F002_CAGTTAGGTTAGTCGT	VIIIa_M001_GTAACACGTTAGAGTA	AN1c_M002_TCAAGCATCTGCGGCA	PRMc_F002_ACTACGATCACCTCGT	IXa_M003_TAATTCCAGGCAGGTT	IIIa_M001_TGTTCATGTCGCGTCA	IIb_F001_CTCTCAGCACTCCTGT	DECa_F002_GCGAGAAGTCTAACTG	PFc_M001_AGGAGGTCACTGGCCA	Xb_F001_GACTCAAAGTGCACAG	Vl_M006_GTTACAGAGTGGTTCT	VIb_M002_ACTGATGGTGTGCTTA	PFa_F002_TGGTAGTAGCATCTTG	PFb_M001_TAACTTCGTCTGCAAT	PRMc_M006_TGTTCCGTCCTTTGAT	VIc_M006_ACTGATGCAGGAACCA	IIb_F001_AGACCATAGCGCTTCG	AN2b_M006_TCGCTCAGTGGCACTC	VIIIb_M001_TATCTTGCACCTGTCT	PFd_M001_AGGACGAGTGAGTAAT	Ia_M001_GCAGCTGCACAAGCCC	SIMc_M002_CTCCAACAGAGCCCAA	VIc_M002_CCTCTCCTCCTACCGT	DECa_F002_TTCGATTAGGTTATAG	VIIb_M002_GACGTTACAAAGGCTG	SIMa_M002_ATAGACCCATAGGTTC	VI_F001_CCGGACAAGAGTTGCG	IIIa_M001_GTAAGTCGTATCGTGT	AN1a_F002_CATCAAGAGCCGTTAT	VI_F001_TTGAGTGCACAAGTTC	PFa_M001_AAGACAACAATACCTG	AN1c_M002_CATCGTCGTGACCGTC	VIc_M002_CTGTATTTCTCGACGG	III_F001_GCGTGCACACTCAGAT	VIIa_F002_CCGATGGGTGAGCTCC	IIa_F001_GACTATGAGGTCGTAG	CULb_M006_AGGACTTGTCGAGCTC	PRMb_M006_GCTTGGGCATTGCTGA	COPc_M002_TGCTCGTCATCGTGCG	Xa_M006_TTGACCCAGTAAAGCT	IIb_F001_ACCCTTGTCCTAGAGT	DECc_M006_GAGTCATCAAGTGGAC	PRMe_M006_CTCAGGGCACGCTGCA	IIa_M001_TGTGTGATCTCGTCGT	IV_M006_AGTCAACAGAAGCGCT	PRMa_F002_GTTATGGTCATACGAC	VIa_M002_ATACCTTAGTCTAACC	Xa_F001_CATGCGGGTTCTCAGA	AN2b_M002_GGGCTCAAGCCTGAAG	AN1a_F002_ACTTCGCAGTTACTCG	PFb_M001_ACCTGTCAGAAATTGC	PFb_M001_CTGTCGTGTGACACAG	VIIb_M006_CAAAGAATCGCGATCG	IIIb_F001_TTATTGCAGAACAGGA	VIIb_F002_GCCGTGACATTATGCG	DECa_M006_CAGATCATCGAGTTGT	PFa_F002_AACAGGGCAATACCCA	X_M001_CCCGAAGCAAGCGGAT	VIc_M006_GTCATGAAGGTATCTC	Ia_M001_TTACGTTCACCAGTAT	IXa_F002_TGAGACTTCTAAGAAG	VIIb_M002_ATTCCCGCAGTCGGAA	VIIb_M002_CTCCATGAGATGCAGC	Xb_F001_CGATGCGTCCACCCTA	COPa_F002_TTGCCTGGTCGTGTTA	Fc_M006_TCGCACTTCGCTGCGA	VIIIb_M001_CAGCAATCAAATCGGG	AN2b_F002_GGGCTCAGTAGGTACG	VIc_M002_AGGAAATGTCTCACAA	AN2b_F002_TCATGCCCATGGCACC	SIM_F001_CAGTTCCAGAGGTCAC	SIMa_M002_TTCAATCTCGAAACAA	PRMe_M002_CTGCCATTCCGCGGAT	SIMa_M006_CCGGGTACAGGGACTA	DECc_M006_GTAGGAGTCAACCCGG	PRMb_M002_TCCATGCTCTACAGGT	PRMd_M002_CCAATTTGTATCAGCT	PFd_M001_GAATCACCAGGCACAA	AN2b_F002_CCTCCTCTCGGAATGG	AN2b_F002_GTGCACGTCAGAGCGA	VIIIc_F002_CGTGATATCTCTGGTC	VIb_M002_ATCATTCAGTATCTGC	PRMa_M002_TGGGCGTTCGATCCAA	PF_M006_CAGATCATCGCTAAAC	VIe_M002_GCAGCCATCGCAGTCG	VIIa_M006_AATTCCTAGTAACGTA	IXc_M003_AGAGCCCTCATTGCGA	PFb_F002_CACGAATGTGTAACGG	VIa_M002_CGTAAGTCATGGTACT	COPa_M002_GGTGTTAAGCTGTTAC	Ia_M001_ACTTTCAGTATTCCGA	I_M006_TCACACCAGTGTAGAT	VI_F001_TAATTCCTCGTAGCCG	VIIIb_F002_ACATTTCCATTGGATC	SIM_F001_AGCTCAAGTCAATGGG	Vc_M002_TAGTGCACATGGAGAC	AN2c_M006_TTTGGAGTCATGCGGC	Vc_M002_CTACCCAGTGTCTAAC	Vb_M002_GATTCTTCATTCACCC	Va_M002_GTTTGGAGTTGCCATA	Vb_M002_TCTACCGTCAAGAATG	VIb_M006_CCTCCAAGTGAACCGA	Xa_F001_CCACCATTCCCAGCGA	PFb_F002_TGACAGTAGCCTCTCT	VIIId_F002_GAGTGAGCAACACTAC	VIIIb_M001_GTTTACTCACTGCTTC	AN2c_M002_TATATCCTCAGTCTTT	PFb_M006_TAGCACATCTTCTGTA	AN2a_M006_AGTCAACTCATCACCC	IIb_F001_GTAGGAGAGGCGACAT	DECb_M006_GTGAGCCAGGAACATT	VIIIb_M001_CGTAGTACAAATGCGG	AN2a_M002_AGGATAATCACTAGCA	F_M001_TCTCCGAAGCAGCAGT	VIIIb_F002_TCATTACGTCGAAACG	Fa_M006_AGCGATTCAAATACAG	COP_M006_AAGTGAAGTTGTGGCC	AN2c_M006_AACAGGGAGTGCCAGA	IXa_M003_TGGTTAGCAGCTTTCC	PF_M006_CCTCACATCGGACCAC	Vc_M002_CTCCACAAGCGGCTCT	AN1b_M006_TGTCCCACATCGGCCA	SIM_F001_TGGTAGTTCGCGTTTC	IXb_F002_CACCGTTGTGAGTGAC	VIIIc_F002_CTCTCGAAGAGTGTGC	AN2c_M002_CTGCTCAGTCGATTTG	AN2b_M002_TTCATGTGTTACAGCT	VIId_M002_GGTGAAGCAAGGTACG	VIIIc_F002_CCACCATTCACCTGTC	IV_M006_CCTCACACAAAGAGTT	VIc_M002_AGGATCTAGGTATTGA	AN2a_M006_TCGTAGAAGCTCTGTA	AN2a_M006_AGATCCATCAATGTCG	IIa_F001_GTTAGACCATCTATCT	COPa_F002_CTCCACAGTCTATGAC	IXa_M003_AGGCCACGTCGCGTCA	VIa_M006_CACTTCGAGAAACTAC	IXa_M003_GTAGGAGCAATAGTCC	PRMe_M006_AGTCTCCAGAGAGTGA	PRMb_M002_CTACAGAGTATCGTAC	VI_F001_AACAAAGAGGCTGTAG	IIIb_F001_CTGCTCAAGCCTAACT	IIIb_F001_GTGGAAGCAGCATTGT	F_F001_TGTGTGAAGCCACAAG	AN2a_M002_TGGTAGTGTGGATCGA	I_F001_TTCTTGATCCCGATCT	AN1a_M006_GTGGGAAGTACGACAG	PFc_F002_AACCATGGTCATGCAT	VIIIa_F002_CGTTCTGTCGATACTG	VIb_M006_TCTGCCAAGGACAGTC	VIb_M006_ATTCTTGCAACTGGTT	VIb_M006_GGATCTAAGGATTCCT	AN1b_M002_TACCGAATCAGCGTCG	II_M006_AGTGACTGTCAGGAGT	VI_F001_AACACACGTGACTAAA	IIa_M001_AGGGTGATCTATCGGA	VIIId_F002_TGTTACTAGCCTCTTC	IXc_M003_AGACACTTCCCAGCGA	AN2c_F002_CCGTGAGAGGCACCAA	VIc_M002_TCTATCATCCATAGGT	VIb_M002_ACCATTTAGACTTCCA	SIM_F001_TTCGGTCCATGTGTCA	VIb_M006_CTCATTATCAGCCCAG	IXb_M003_ACACTGATCATGACAC	IIb_M001_TTGGGCGCACAATTCG	F_M006_GGAGCAAAGCTAATCC	IIIa_M001_TGCGGGTCACACACTA	Vb_M002_GTCATCCCAGCTGTTA	PF_M006_CCATAAGAGATCCTAC	AN1c_M002_GCGGAAATCACTCGAA	PF_M006_AGACCATGTATGGTAA	Fc_M006_CCTACGTTCTCGAGTA	PRMc_F002_TGGAACTCAAAGCAAT	VIIIc_F002_GGAGCAATCTACCCAC	AN2c_F002_TTACAGGTCGCCAGTG	PRMa_M006_AACCAACGTAGCGTTT	AN2c_F002_GGGTGAAGTCATCACA	AN2c_M006_TTAGGGTTCTAACACG	PF_M006_GTCGAATGTAGGCTCC	Vc_M002_GCCTGTTGTCTGGTTA	Ib_M001_GTGATGTGTCGGTGTC	PRMa_M006_TACAGGTCATCGTCCT	AN2b_F002_TCGACGGCAAGCTGTT	VIc_M006_CGGAATTCAGAGTTGG	PFb_M006_TGTTGAGAGCGCATCC	Ia_M001_GCCAGGTAGCAGTAAT	F_M006_TCGGTCTTCTTGCAGA	AN1b_F002_TCATTACAGACTTCGT	Vb_M002_ACGATGTTCTGGGTCG	AN2e_M006_GCATCGGAGCGCTGCT	IXb_M003_CCATCACCATACAGCT	IXb_M003_CTCCATGGTGGATTTC	IXa_M003_AGGGTCCTCTTTGCGC	VIIb_M006_GTAGAAAGTCCGTTTC	IXc_M006_GACCTTCTCATTGGTG	PRMe_M002_GCTTCACAGGGTACGT	IXc_F002_ACGGAAGGTACAAGTA	PRMb_M002_CTATAGGCACAAAGTA	VIIb_M006_CCACCATGTCCTTAAG	PRMa_M006_ACGTCCTAGCCTATTG	VIIb_M002_ACGGGTCCACCGCTGA	AN2a_M002_TATACCTGTTGGAGAC	IIa_M001_TGCAGATTCTCATTGT	PRMf_M006_TAACACGTCACCTTAT	IXc_M006_TGTTCATCACTGGCCA	PFb_M001_AGGTTACCAACCAATC	VIIIb_F002_TTTCAGTTCCATCCGT	AN2a_F002_TAGGGTTCAATGAGCG	AN2_M006_AGAGCCCCAACTCGAT	AN2e_M006_TTGCATTAGACTCGAG	PRMf_M006_TGTCCACTCGGTGCAC	AN1b_M006_AACCCAAGTTGGATCT	AN1c_F002_CTGAGGCGTCGAGCTC	II_M006_GTTTGGAAGTGCGACA	PFb_F002_CAAGAGGAGTTCACTG	PF_M006_ATGCCTCAGGAAGTAG	VIb_M002_TTCTCTCCATCCTCAC	X_M001_ACGATCATCAAGTTGC	VIIId_F002_AGATCCAAGTTAGAAC	IIa_F001_GCATGATGTATAGCTC	PFc_M001_CATACAGAGGCAGGGA	PF_M006_TACGTCCTCTGTTCAT	AN1_M006_CCGATCTTCGTAGAGG	AN2d_M006_GCCATTCCATGGGAAC	F_F001_CCCTCTCCATACCAGT	AN1c_F002_GAGTTACAGTATGAAC	IXb_M006_TCAGTGACAAGGTTGG	Xb_F001_TGGATGTCAGACAATA	VIa_M006_GACCCTTGTACCGCGT	PRMa_F002_CTGGCAGGTTTGTTCT	PF_M006_CATACCCGTACTGAGG	Ib_M001_ATGGTTGTCGGTCGAC	SIM_F001_ATATCCTAGTTGGAGC	PRMa_F002_GGTAATCGTCTACTGA	AN2e_M006_CTCAAGACACAACGCC	VId_M002_AACCTGATCGGTGAAG	AN2c_M002_TGTACAGTCTTAGTTC	AN1a_M002_GAATCGTGTGCTATTG	DECc_M006_ATCACGAGTAGCGAGT	AN2e_M006_GACTCAAGTTTGTGGT	IV_M006_CTGAGGCGTTCCAAAC	Ib_M001_GACAGCCTCCGTTGAA	SIMc_M002_AAGTGAATCAGAACCT	IXc_M003_GCAACCGAGATGCTAA	Xa_F001_TACTGCCGTCATAGTC	Xa_F001_TCGAAGTCACTTGTCC	Xb_F001_CATGCCTCAGACGCTC	IXa_F002_TCATACTGTCACTGAT	IXc_M003_CGGGCATGTTCGGTTA	VIIa_M006_AGGTCTAAGAGCATAT	PFc_M001_ATTACCTAGTTACTCG	VIIb_F002_TTTGGTTAGGTTGCCC	F_F001_TATATCCTCGTGCGAC	IXa_M003_AAGTTCGGTGATACCT	PFb_F002_GAGTCATTCGCGTAGC	PFa_F002_AGGGCCTAGGAACGTC	AN2b_M002_AACCACATCCACCTGT	Xb_F001_AGGGTCCTCATTTCCA	PRMb_M006_GAGTCATTCGGTCTAA	PFd_M001_GTAGAGGAGGTTAAAC	IIa_F001_CGTCAAAAGAATCCCT	AN2c_F002_TAAGTCGCAACCAGAG	VIIId_F002_GGTAGAGCACGCACCA	I_F001_TCGGGCACATGGAGAC	I_F001_TGACCCTGTAGACGGT	Fc_M006_GTTGTGACATCCGAGC	Ib_M001_GACCCTTTCATACGGT	I_F001_GTAGAAAGTTCCACAA
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diff --git a/tools/spacexr/test-data/st_count.tabular b/tools/spacexr/test-data/st_count.tabular
new file mode 100644
index 00000000000..5a05729f1e3
--- /dev/null
+++ b/tools/spacexr/test-data/st_count.tabular
@@ -0,0 +1,379 @@
+TTGGACGTTTCAAT	CACGGCCATATTGC	CGCCCCCCACCCCT	CCCCCCCCATTGAA	CGCTTGGCATTTAC	CGTGAGTTTCTCCT	ATTCAGTCGCATTA	CCAACTCCCCTACT	TTAAGGCCTAGGCT	GACCTTCAGAGTAA	TGAAGGTTTTATGC	GCCGGATCTTCTTT	AACAGCGTTCCTTG	CTTCAAACATGTCA	AGACCCCCACGCCG	AAGTACCCGCCCTG	ACTCTTGCTCGCGC	GTAACCTAGATCTG	GTCATAACGACAGG	TGTATCTCCGAGTG	TCCAGCTGTTCGAA	GAACATGGGTATTG	GCCAGTATCCGAAG	TGTTGTAGCTAAAG	ATGCCTCAGTCCTG	ATAGGATATATCTT	TGCCTATATTACGC	ATTTGGACGCATGC	AAGCCCCCCGAGCC	GTTAGGCGTCCCGC	CAGCGGGCGATTCC	TAGGGTGGGCTGTA	GGGGACGAATAGTG	CTCTCCTCATGTCT	GTAGATACAGATTC	CGGAAACTTGACAC	GATCCTGCATTGTT	TAAGGGTAGATTTT	GGCTCGAGTTTAAG	CTGGTTTCCCCTTG	TCTTACCATCAGTG	AGGAGGGTCCATTT	TTTGATACGCCAGT	TTGACCGTTCTTCC	TTCTCAGTCTCCTT	CATTTAATGTCGTG	CCCTTTCACAGCGA	CCTACCAAAGCTCT	AGAGGTTATCTCGA	TAATCGGAAGACTC	CTTGCACCTAGAAC	TACGGACAGTTACT	AATACTCACTCATT	GGCCTAACTCCACA	GCCCCGGAATCCCT	TCCCACGCCGCGTG	TACGGGTCAGTTCC	TATCTCCGTGCAAC	TGTAGGCTTCCCTT	GTCTGAGCACTGTC	TATTGCATCTCTGT	TAGCACATAATCCC	AAGCCTGACCGCAC	GTATGGAGCATACT	CAAACATGAGATTC	GTTTCCAATATTAG	CGGCTCCGTAGAAC	TAAGTTGTGAGGCC	GTGCCCCTATCCTG	ATGTGCCACATCGG	CCGCCGTCTCGATG	GAACTCAGTCTTGA	CAGCTCGTGCTTGA	GGCTGGCTGAGGCC	TAGGCTGAAGACTG	CTTCCGGCATGTCC	GCCCCCCATCTGCT	GATTGGTCCGGCTG	CCGATTGGAGATCA	AGCTTATTACGTTG	TGGCCTGGTTATCC	AAGGTATCTCAACA	CGTTACACACCTCA	TGGTTGAGCGATCT	GTGGAACCAGCCAA	GTTCTTAGATCCTT	CGGCCGTGCCCACC	TTCTGGTTTCTGGC	CTGATTGTGCTCAT	CACATATGCCTCCT	TATCTGTGAAGGAC	TGACATATTCATCT	CGGCTGGCTCGACC	AAGGCTCTACATCA	TATGCCCAGGACAG	ATGAGTCCACATCT	ATCTTTCCTTCAAA	TAGTCCCCATCCGC	ACACTGATCTTGTC	CTTTTGCTCCGGAA
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