diff --git a/tools/celesta/.shed.yml b/tools/celesta/.shed.yml
new file mode 100644
index 0000000..09269c2
--- /dev/null
+++ b/tools/celesta/.shed.yml
@@ -0,0 +1,15 @@
+owner: goeckslab
+description: "Cell type identification with spatial information"
+long_description: |
+ CELESTA (CELl typE identification with SpaTiAl information) is an
+ algorithm aiming to perform automate cell type identification for
+ multiplexed in situ imaging data. CELESTA makes use of both protein
+ expressions and cell spatial neighborhood information from segmented
+ imaging data for the cell type identification.
+categories:
+ - Imaging
+ - Proteomics
+exclude:
+ - dependencies
+remote_repository_url: https://github.com/goeckslab/tools-mti/tree/main/tools/celesta
+homepage_url: https://github.com/plevritis-lab/CELESTA
diff --git a/tools/celesta/celesta.xml b/tools/celesta/celesta.xml
new file mode 100644
index 0000000..06b9b7f
--- /dev/null
+++ b/tools/celesta/celesta.xml
@@ -0,0 +1,270 @@
+
+ Cell type identification with spatial information
+
+ macros.xml
+
+
+
+ echo "@VERSION@"
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+ runmode['selected_mode'] == "plot_expression"
+
+
+ runmode['selected_mode'] == "assign_cells"
+
+
+ runmode['selected_mode'] == "assign_cells" and runmode['options']['save_rds']
+
+
+
+ runmode['selected_mode'] == "assign_cells" and len(runmode['plot_cells']) != 0
+
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+ CD3+ T cells –> CD4+ T cells. The third number is a number assigned to the cell type,
+ i.e, cell type number. The middle number tells the previous lineage cell type number for the current cell type.
+ For example, the middle number for CD3+ T cells is 5, because it is a subtype of immune cells which have cell
+ type number assigned to 5.
+
+(3) Starting from column three, each column is a protein marker. If the protein marker is known to be expressed
+ for that cell type, then it is denoted by “1”. If the protein marker is known to not express for a cell type,
+ then it is denoted by “0”. If the protein marker is irrelevant or uncertain to express for a cell type,
+ then it is denoted by “NA”.
+
+`Name of anndata.obs key containing cell or nucleus centroid X position` -- if using output from MCMICRO, this would be 'X_centroid'
+
+`Name of anndata.obs key containing cell or nucleus centroid Y position` -- if using output from MCMICRO, this would be 'Y_centroid'
+
+`Choose whether to filter cells` -- Boolean whether to filter out cells with extreme low or high marker intensity that fall outside of thresholds (`CELESTA::FilterCells()`)
+
+`Set the low threshold for filtering cells` -- high_marker_threshold param in `CELESTA::FilterCells()`
+
+`Set the high threshold for filtering cells` -- low_marker_threshold param in `CELESTA::FilterCells()`
+
+**Run modes**
+
+1. Plot expression probabilities for markers in the cell type signature matrix
+
+ This run mode generates marker expression probability plots for every marker in the cell-type signature matrix.
+
+ **Additional inputs**
+
+ `Specify the point size for plotting cells` -- passed to `ggplot2::geom_point()` size param
+
+ `Specify the height of the figure (inches)` -- passed to `ggplot2::ggsave()` height param
+
+ `Specify the width of the figure (inches)` -- passed to `ggplot2::ggsave()` width param
+
+ **Outputs**
+
+ Collection of `.png` figures showing marker intensity probabilities as spatial scatter plots
+
+2. Run the cell type assignment
+
+ **Additional inputs**
+
+ `Define the maximum iterations allowed in the EM algorithm per round` -- passed to `CELESTA::AssignCells()` max_iteration param
+
+ `Define an ending condition for the EM algorithm` -- passed to `CELESTA::AssignCells()` cell_change_threshold param
+
+ `Provide a file mapping low/high anchor and index cell assignment thresholds to cell types` -- comma separated text file containing following information and formatting:
+
+(1) First column contains cell types to be inferred (same order as the cell type signature matrix)
+ Second column is named `anchor` and contains high or low thresholds for anchor cells
+ Third column is named `index` and contains high or low thresholds for index cells
+
+(2) In the `CELESTA::AssignCells()` function, it requires four vectors to define the high and low thresholds for each cell type. The length of the vector equals to the
+ total number of cell types defined in the cell-type signature matrix. We would suggest start with the default thresholds and modify them by comparing the results
+ with the original staining. The two vectors are required for defining the “high_expression_threshold”, one for anchor cells and one for index cells (non-anchor cells).
+ The thresholds define how much the marker expression probability is in order to be considered as expressed.
+
+(3) For the low thresholds, Normally 1 is assigned to this value unless there are a lot of doublets or co-staining in the data. The Low expression threshold default
+ values in general are robust, and thus we recommend testing the High expression threshold values.
+
+`Also save CELESTA object as RDS file` -- Boolean whether to output an RDS file in addition to the default h5ad output
+
+`Plot combinations of resulting cell type assignments` -- specify any combination of cell types from the cell type signature matrix to plot. This is a repeat element, and one plot will be generated per repitition. There are additional params to control plot aesthetic attributes
+
+**Outputs**
+
+`CELESTA assign cells output` -- The primary output, an h5ad file, with new columns containing cell type information. New columns are prepended with `celesta_`
+
+`CELESTA object RDS` -- optionally output CELESTA object as RDS for downstream analysis in R
+
+Optional collection of `.png` figures of spatial scatter plots color annotated by cell type assignment
+
+Visit github.com/plevritis-lab/CELESTA for full documentation
+
+ ]]>
+
+
+
diff --git a/tools/celesta/celesta_assign_cells.R b/tools/celesta/celesta_assign_cells.R
new file mode 100644
index 0000000..49d4b1e
--- /dev/null
+++ b/tools/celesta/celesta_assign_cells.R
@@ -0,0 +1,153 @@
+# ---------------------------------------------------------------------------------
+# The main algorithim for CELESTA cell type assignment
+# ---------------------------------------------------------------------------------
+
+suppressWarnings(suppressMessages(library(janitor)))
+suppressWarnings(suppressMessages(library(optparse)))
+suppressWarnings(suppressMessages(library(dplyr)))
+suppressWarnings(suppressMessages(library(anndataR)))
+suppressWarnings(suppressMessages(library(Rmixmod)))
+suppressWarnings(suppressMessages(library(spdep)))
+suppressWarnings(suppressMessages(library(ggplot2)))
+suppressWarnings(suppressMessages(library(reshape2)))
+suppressWarnings(suppressMessages(library(zeallot)))
+suppressWarnings(suppressMessages(library(CELESTA)))
+
+### Define command line arguments
+option_list <- list(
+ make_option(c("-i", "--imagingdata"), action = "store", default = NA, type = "character",
+ help = "Path to imaging data"),
+ make_option(c("-p", "--prior"), action = "store", default = NA, type = "character",
+ help = "Path to prior marker info file"),
+ make_option(c("-x", "--xcol"), action = "store", default = NA, type = "character",
+ help = "Name of column in adata.obs containing X coordinate"),
+ make_option(c("-y", "--ycol"), action = "store", default = NA, type = "character",
+ help = "Name of column in adata.obs containing Y coordinate"),
+ make_option(c("--filter"), action = "store_true", type = "logical", default = FALSE,
+ help = "Boolean to filter cells or not (default: no filtering)"),
+ make_option(c("--highfilter"), action = "store", default = 0.9, type = "double",
+ help = "High marker threshold if filtering cells (default: 0.9)"),
+ make_option(c("--lowfilter"), action = "store", default = 0.4, type = "double",
+ help = "Low marker threshold if filtering cells (default: 0.4)"),
+ make_option(c("--maxiteration"), action = "store", default = 10, type = "integer",
+ help = "Maximum iterations allowed in the EM algorithm per round"),
+ make_option(c("--changethresh"), action = "store", default = 0.01, type = "double",
+ help = "Ending condition for the EM algorithm"),
+ make_option(c("--highexpthresh"), action = "store", default = "default_high_thresholds", type = "character",
+ help = "Path to file specifying high expression thresholds for anchor and index cells"),
+ make_option(c("--lowexpthresh"), action = "store", default = "default_low_thresholds", type = "character",
+ help = "Path to file specifying low expression thresholds for anchor and index cells")
+)
+
+### Functions
+anndata_to_celesta <- function(input_adata, x_col, y_col) {
+
+ #' Function to convert anndata object to dataframe readable by CELESTA
+ #' Coordinates columns in adata.obs are renamed to "X" and "Y", and placed at beginning of dataframe
+ #' Marker intensities are concatted columnwise to the X and Y coords. cols: X,Y,Marker_1,...Marker N
+
+ # initialize output as dataframe from adata.obs
+ celesta_input_dataframe <- data.frame(input_adata$obs)
+
+ # subset to X and Y coordinates from obs only
+ celesta_input_dataframe <- celesta_input_dataframe %>%
+ dplyr::select({{x_col}}, {{y_col}})
+
+ # rename X,Y column names to what CELESTA wants
+ colnames(celesta_input_dataframe) <- c("X", "Y")
+
+ # merge X,Y coords with marker intensities from adata.X
+ x_df <- data.frame(input_adata$X)
+ colnames(x_df) <- input_adata$var_names
+ celesta_input_dataframe <- cbind(celesta_input_dataframe, x_df)
+
+ return(celesta_input_dataframe)
+}
+
+### Main
+# parse args
+opt <- parse_args(OptionParser(option_list = option_list))
+
+# read anndata, convert to celesta format
+adata <- read_h5ad(opt$imagingdata)
+celesta_input_df <- anndata_to_celesta(adata, x_col = opt$xcol, y_col = opt$ycol)
+
+# read prior marker info
+prior <- read.csv(opt$prior, check.names = FALSE)
+
+# clean prior names and input dataframe names
+prior <- janitor::clean_names(prior, case = "all_caps")
+celesta_input_df <- janitor::clean_names(celesta_input_df, case = "all_caps")
+
+# instantiate celesta object
+CelestaObj <- CreateCelestaObject(
+ project_title = "",
+ prior_marker_info = prior,
+ imaging_data_file = celesta_input_df
+)
+
+# if filtering is specified, filter out cells outside high and low thresholds
+if (opt$filter) {
+ print("filtering cells based on expression")
+ CelestaObj <- FilterCells(CelestaObj,
+ high_marker_threshold = opt$highfilter,
+ low_marker_threshold = opt$lowfilter)
+} else {
+ print("Proceeding to cell type assignment without cell filtering")
+}
+
+# check for non-default expression threshold files
+if (opt$highexpthresh != "default_high_thresholds") {
+ # read high thresholds
+ print("Using custom high expression thresholds")
+ high_expression_thresholds <- read.csv(opt$highexpthresh)
+ hi_exp_thresh_anchor <- high_expression_thresholds$anchor
+ hi_exp_thresh_index <- high_expression_thresholds$index
+} else {
+ print("Using default high expression thresholds -- this may need adjustment")
+ hi_exp_thresh_anchor <- rep(0.7, length = 50)
+ hi_exp_thresh_index <- rep(0.5, length = 50)
+}
+
+if (opt$lowexpthresh != "default_low_thresholds") {
+ # read low thresholds
+ print("Using custom low expression thresholds")
+ low_expression_thresholds <- read.csv(opt$highexpthresh)
+ low_exp_thresh_anchor <- low_expression_thresholds$anchor
+ low_exp_thresh_index <- low_expression_thresholds$index
+} else {
+ print("Using default low expression thresholds")
+ low_exp_thresh_anchor <- rep(0.9, length = 50)
+ low_exp_thresh_index <- rep(1, length = 50)
+}
+
+# run cell type assignment
+CelestaObj <- AssignCells(CelestaObj,
+ max_iteration = opt$maxiteration,
+ cell_change_threshold = opt$changethresh,
+ high_expression_threshold_anchor = hi_exp_thresh_anchor,
+ low_expression_threshold_anchor = low_exp_thresh_anchor,
+ high_expression_threshold_index = hi_exp_thresh_index,
+ low_expression_threshold_index = low_exp_thresh_index,
+ save_result = FALSE)
+
+# save object as an RDS file for cell type plotting
+# for the time being, this is not exposed to Galaxy
+saveRDS(CelestaObj, file = "celestaobj.rds")
+
+# rename celesta assignment columns so they are obvious in output anndata
+celesta_assignments <- CelestaObj@final_cell_type_assignment
+celesta_assignments <- janitor::clean_names(celesta_assignments)
+colnames(celesta_assignments) <- paste0("celesta_", colnames(celesta_assignments))
+
+# merge celesta assignments into anndata object
+adata$obs <- cbind(adata$obs, celesta_assignments)
+
+# print cell type value_counts to standard output
+print("----------------------------------------")
+print("Final cell type counts")
+print(adata$obs %>% dplyr::count(celesta_final_cell_type, sort = TRUE))
+print("----------------------------------------")
+
+# write output anndata file
+write_h5ad(adata, "result.h5ad")
diff --git a/tools/celesta/celesta_plot_cells.R b/tools/celesta/celesta_plot_cells.R
new file mode 100644
index 0000000..51e47ea
--- /dev/null
+++ b/tools/celesta/celesta_plot_cells.R
@@ -0,0 +1,76 @@
+# ---------------------------------------------------------------------------------
+# Plot assigned cell type combinations with CELESTA
+# ---------------------------------------------------------------------------------
+
+suppressWarnings(suppressMessages(library(janitor)))
+suppressWarnings(suppressMessages(library(optparse)))
+suppressWarnings(suppressMessages(library(dplyr)))
+suppressWarnings(suppressMessages(library(anndataR)))
+suppressWarnings(suppressMessages(library(Rmixmod)))
+suppressWarnings(suppressMessages(library(spdep)))
+suppressWarnings(suppressMessages(library(ggplot2)))
+suppressWarnings(suppressMessages(library(reshape2)))
+suppressWarnings(suppressMessages(library(zeallot)))
+suppressWarnings(suppressMessages(library(CELESTA)))
+
+# define command line args
+option_list <- list(
+ make_option(c("-r", "--rds"), action = "store", default = "celestaobj.rds", type = "character",
+ help = "Path to CelestaObj RDS"),
+ make_option(c("-p", "--prior"), action = "store", default = NA, type = "character",
+ help = "Path to prior marker info file"),
+ make_option(c("-c", "--celltypes"), action = "store", default = NA, type = "character",
+ help = "Comma-separated list of cell types to plot"),
+ make_option(c("-s", "--size"), action = "store", default = 1, type = "double",
+ help = "Point size for plotting"),
+ make_option(c("--width"), action = "store", default = 12, type = "integer",
+ help = "Width of plot (inches)"),
+ make_option(c("--height"), action = "store", default = 12, type = "integer",
+ help = "Height of plot (inches)"),
+ make_option(c("--dpi"), action = "store", default = 300, type = "integer",
+ help = "DPI (dots per inch) of plot")
+)
+
+# parse args
+opt <- parse_args(OptionParser(option_list = option_list))
+
+CelestaObj <- readRDS(opt$rds)
+cell_types_to_plot <- strsplit(opt$celltypes, ",")[[1]]
+
+# read prior marker info
+prior <- read.csv(opt$prior, row.names = 1)
+
+# get indices of cell types to plot from the prior marker table
+cell_type_indices <- which(row.names(prior) %in% cell_types_to_plot)
+
+print(cell_types_to_plot)
+print(cell_type_indices)
+
+print(row.names(prior))
+
+# create output directory if it doesn"t already exist
+dir.create("cell_assign_plots")
+
+# create the cell type plot
+g <- PlotCellsAnyCombination(cell_type_assignment_to_plot = CelestaObj@final_cell_type_assignment[, (CelestaObj@total_rounds + 1)],
+ coords = CelestaObj@coords,
+ prior_info = prior_marker_info,
+ cell_number_to_use = cell_type_indices,
+ test_size = 1,
+ save_plot = FALSE)
+
+# create a unique output name for the plot based on the input cell types
+cell_types_cleaned <- paste(make_clean_names(cell_types_to_plot), collapse = "")
+output_name <- paste(c("plot_cells_", cell_types_cleaned, ".png"), collapse = "")
+
+# save to subdir
+# FIXME: may want to expose plotting params to galaxy
+ggsave(
+ path = "cell_assign_plots",
+ filename = output_name,
+ plot = g,
+ width = opt$width,
+ height = opt$height,
+ units = "in",
+ dpi = opt$dpi
+)
diff --git a/tools/celesta/celesta_plot_expression.R b/tools/celesta/celesta_plot_expression.R
new file mode 100644
index 0000000..bbcb420
--- /dev/null
+++ b/tools/celesta/celesta_plot_expression.R
@@ -0,0 +1,108 @@
+# --------------------------------------------------------------------------------------------
+# Plot marker expression probabilities for cell assignment parameter optimization with CELESTA
+# --------------------------------------------------------------------------------------------
+
+suppressWarnings(suppressMessages(library(janitor)))
+suppressWarnings(suppressMessages(library(optparse)))
+suppressWarnings(suppressMessages(library(dplyr)))
+suppressWarnings(suppressMessages(library(anndataR)))
+suppressWarnings(suppressMessages(library(Rmixmod)))
+suppressWarnings(suppressMessages(library(spdep)))
+suppressWarnings(suppressMessages(library(ggplot2)))
+suppressWarnings(suppressMessages(library(reshape2)))
+suppressWarnings(suppressMessages(library(zeallot)))
+suppressWarnings(suppressMessages(library(CELESTA)))
+
+### Define command line arguments
+option_list <- list(
+ make_option(c("-i", "--imagingdata"), action = "store", default = NA, type = "character",
+ help = "Path to imaging data"),
+ make_option(c("-p", "--prior"), action = "store", default = NA, type = "character",
+ help = "Path to prior marker info file"),
+ make_option(c("-x", "--xcol"), action = "store", default = NA, type = "character",
+ help = "Name of column in adata.obs containing X coordinate"),
+ make_option(c("-y", "--ycol"), action = "store", default = NA, type = "character",
+ help = "Name of column in adata.obs containing Y coordinate"),
+ make_option(c("--filter"), action = "store_true", type = "logical", default = FALSE,
+ help = "Boolean to filter cells or not (default: no filtering)"),
+ make_option(c("--highfilter"), action = "store", default = 0.9, type = "double",
+ help = "High marker threshold if filtering cells (default: 0.9)"),
+ make_option(c("--lowfilter"), action = "store", default = 0.4, type = "double",
+ help = "Low marker threshold if filtering cells (default: 0.4)"),
+ make_option(c("-s", "--size"), action = "store", default = 1, type = "double",
+ help = "Point size for plotting"),
+ make_option(c("--width"), action = "store", default = 5, type = "integer",
+ help = "Width of plot (inches)"),
+ make_option(c("--height"), action = "store", default = 4, type = "integer",
+ help = "Height of plot (inches)")
+)
+
+### Functions
+anndata_to_celesta <- function(input_adata, x_col, y_col) {
+
+ #' Function to convert anndata object to dataframe readable by CELESTA
+ #' Coordinates columns in adata.obs are renamed to "X" and "Y", and placed at beginning of dataframe
+ #' Marker intensities are concatted columnwise to the X and Y coords. cols: X,Y,Marker_1,...Marker N
+
+ # initialize output as dataframe from adata.obs
+ celesta_input_dataframe <- data.frame(input_adata$obs)
+
+ # subset to X and Y coordinates from obs only
+ celesta_input_dataframe <- celesta_input_dataframe %>%
+ dplyr::select({{x_col}}, {{y_col}})
+
+ # rename X,Y column names to what CELESTA wants
+ colnames(celesta_input_dataframe) <- c("X", "Y")
+
+ # merge X,Y coords with marker intensities from adata.X
+ x_df <- data.frame(input_adata$X)
+ colnames(x_df) <- input_adata$var_names
+ celesta_input_dataframe <- cbind(celesta_input_dataframe, x_df)
+
+ return(celesta_input_dataframe)
+}
+
+### Main
+# parse args
+opt <- parse_args(OptionParser(option_list = option_list))
+
+# read anndata, convert to celesta format
+adata <- read_h5ad(opt$imagingdata)
+celesta_input_df <- anndata_to_celesta(adata, x_col = opt$xcol, y_col = opt$ycol)
+
+# read prior marker info
+prior <- read.csv(opt$prior, check.names = FALSE)
+
+# clean prior names, keeping a copy of originals for writing output
+prior_original_names <- colnames(prior)
+prior <- janitor::clean_names(prior, case = "all_caps")
+
+# clean input dataframe names
+celesta_input_df <- janitor::clean_names(celesta_input_df, case = "all_caps")
+
+# instantiate celesta object
+CelestaObj <- CreateCelestaObject(
+ project_title = "",
+ prior_marker_info = prior,
+ imaging_data_file = celesta_input_df
+)
+
+# if filtering is specified, filter out cells outside high and low thresholds
+if (opt$filter) {
+ print("filtering cells based on expression")
+ CelestaObj <- FilterCells(CelestaObj,
+ high_marker_threshold = opt$highfilter,
+ low_marker_threshold = opt$lowfilter)
+} else {
+ print("Proceeding to marker expression plotting without cell filtering")
+}
+
+# create output directory if it does not already exist
+dir.create("marker_exp_plots")
+
+# plot expression probability
+PlotExpProb(coords = CelestaObj@coords,
+ marker_exp_prob = CelestaObj@marker_exp_prob,
+ prior_marker_info = CelestaObj@prior_info,
+ save_plot = TRUE,
+ output_dir = "./marker_exp_plots")
diff --git a/tools/celesta/dependencies/Dockerfile b/tools/celesta/dependencies/Dockerfile
new file mode 100644
index 0000000..3e6d4eb
--- /dev/null
+++ b/tools/celesta/dependencies/Dockerfile
@@ -0,0 +1,33 @@
+FROM jupyter/base-notebook:latest
+
+RUN conda config --add channels bioconda \
+ && mamba install -y \
+ pandas=1.5.3 \
+ anndata \
+ r-optparse \
+ r-janitor \
+ bioconductor-rhdf5 \
+ r-devtools \
+ r-rmixmod \
+ r-spdep \
+ r-reshape2 \
+ r-zeallot \
+ r-colorspace \
+ r-viridisLite \
+ r-RColorBrewer \
+ r-munsell \
+ r-labeling \
+ r-farver \
+ r-nlme \
+ r-scales \
+ r-mgcv \
+ r-isoband \
+ r-gtable \
+ r-s2 \
+ r-rcppeigen \
+ r-ggplot2 \
+ && mamba clean -yaf
+
+RUN R -e "devtools::install_github('plevritis/CELESTA')" \
+ && R -e "devtools::install_github('scverse/anndataR@220f977c15669a22207b37d437fc6d00b060b95f')" \
+ && R -e "devtools::install_github('r-spatial/sf')"
\ No newline at end of file
diff --git a/tools/celesta/macros.xml b/tools/celesta/macros.xml
new file mode 100644
index 0000000..9eae4d6
--- /dev/null
+++ b/tools/celesta/macros.xml
@@ -0,0 +1,39 @@
+
+ 0.0.0.9
+ 0
+ 20.01
+
+
+
+ quay.io/goeckslab/celesta:@TOOL_VERSION@
+
+
+
+
+
+
+
+
+
+
+
+ 10.1038/s41592-022-01498-z
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/tools/celesta/test-data/CD31_VASCULATURE_CYC_19_CH_3_exp_prob.png b/tools/celesta/test-data/CD31_VASCULATURE_CYC_19_CH_3_exp_prob.png
new file mode 100644
index 0000000..1a2de38
Binary files /dev/null and b/tools/celesta/test-data/CD31_VASCULATURE_CYC_19_CH_3_exp_prob.png differ
diff --git a/tools/celesta/test-data/celesta_high_exp_thresholds.csv b/tools/celesta/test-data/celesta_high_exp_thresholds.csv
new file mode 100644
index 0000000..7e69940
--- /dev/null
+++ b/tools/celesta/test-data/celesta_high_exp_thresholds.csv
@@ -0,0 +1,17 @@
+,anchor,index
+vasculature,0.9,0.85
+tumor cells,0,0
+aSMA+ stroma,0.8,0.8
+lymphatics,0.95,0.95
+immune cells,0.1,0
+CD3+ T cells,0.6,0.6
+CD15+ granulocytes,0.7,0.7
+B cells,0.95,0.95
+CD11c+ DCs,1,1
+CD68+CD163+ macrophages,0.7,0.6
+plasma cells,0.7,0.7
+NK cells,0.95,0.95
+CD8+ T cells,0.7,0.7
+CD4+ T cells,0.7,0.7
+CD4+ T cells CD45RO+,0.9,0.7
+Tregs,0.9,0.9
\ No newline at end of file
diff --git a/tools/celesta/test-data/celesta_image.h5ad b/tools/celesta/test-data/celesta_image.h5ad
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index 0000000..9b00e4b
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diff --git a/tools/celesta/test-data/celesta_prior.csv b/tools/celesta/test-data/celesta_prior.csv
new file mode 100644
index 0000000..7ad6795
--- /dev/null
+++ b/tools/celesta/test-data/celesta_prior.csv
@@ -0,0 +1,17 @@
+,Lineage_level,CD31 - vasculature:Cyc_19_ch_3,CD34 - vasculature:Cyc_20_ch_3,Cytokeratin - epithelia:Cyc_10_ch_2,aSMA - smooth muscle:Cyc_11_ch_2,Podoplanin - lymphatics:Cyc_19_ch_4,CD45 - hematopoietic cells:Cyc_4_ch_2,CD15 - granulocytes:Cyc_14_ch_2,CD3 - T cells:Cyc_16_ch_4,CD20 - B cells:Cyc_8_ch_3,CD11c - DCs:Cyc_12_ch_3,CD163 - macrophages:Cyc_17_ch_3,CD68 - macrophages:Cyc_18_ch_4,CD38 - multifunctional:Cyc_20_ch_4,CD56 - NK cells:Cyc_10_ch_4,CD8 - cytotoxic T cells:Cyc_3_ch_2,CD4 - T helper cells:Cyc_6_ch_3,CD45RO - memory cells:Cyc_18_ch_3,FOXP3 - regulatory T cells:Cyc_2_ch_3
+vasculature,1_0_1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+tumor cells,1_0_2,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+aSMA+ stroma,1_0_3,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+lymphatics,1_0_4,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0
+immune cells,1_0_5,0,0,0,0,0,1,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
+CD3+ T cells,2_5_6,0,0,0,0,0,NA,0,1,0,0,0,0,0,0,NA,NA,NA,NA
+CD15+ granulocytes,2_5_7,0,0,0,0,0,NA,1,0,0,0,0,NA,0,0,0,0,NA,0
+B cells,2_5_8,0,0,0,0,0,NA,0,0,1,0,0,0,0,0,0,0,0,0
+CD11c+ DCs,2_5_9,0,0,0,0,0,NA,0,0,0,1,0,0,0,0,0,0,0,0
+CD68+CD163+ macrophages,2_5_10,0,0,0,0,0,NA,0,0,0,0,1,1,0,0,0,0,NA,0
+plasma cells,2_5_11,0,0,0,0,0,NA,0,0,0,0,0,0,1,0,0,0,0,0
+NK cells,2_5_12,0,0,0,0,0,NA,0,NA,0,0,0,0,0,1,0,0,0,0
+CD8+ T cells,3_6_13,0,0,0,0,0,NA,0,NA,0,0,0,0,0,0,1,0,NA,0
+CD4+ T cells,3_6_14,0,0,0,0,0,NA,0,NA,0,0,0,0,0,0,0,1,NA,NA
+CD4+ T cells CD45RO+,4_14_15,0,0,0,0,0,NA,0,NA,0,0,0,0,0,0,0,NA,1,0
+Tregs,4_14_16,0,0,0,0,0,NA,0,NA,0,0,0,0,0,0,0,NA,0,1
\ No newline at end of file
diff --git a/tools/celesta/test-data/plot_cells_vasculature.png b/tools/celesta/test-data/plot_cells_vasculature.png
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