Spatial profiling of benign and malignant melanocytic tumors via RNA-SMI (CosMx)

# Spatial Profiling of Benign and Malignant Melanocytic Tumors via RNA-SMI (CosMx) [https://doi.org/10.5061/dryad.ksn02v7b1](https://doi.org/10.5061/dryad.ksn02v7b1) ## Description of the data and file structure "Slide_1.zip", "Slide_2.zip", "Slide_3.zip", "Slide_4.zip": Each .zip folder contains the RNA-SMI data pertaining to Slides 1-3, which examined 203,472 cells amongst ten melanocytic tumors (exact tumor identity per slide is outlined in fig. S1, with further slide information regarding microscopic field of view distribution outlined in fig. S2). Slide 4 contains the RNA-SMI data examining 84,312 cells including the nevus-melanoma mixed tumor featured in fig. 4 as well as four other melanocytic tumors (one melanoma, one cutaneous metastasis, and two nevi). Specifically, each .zip folder contains the following files and folders: **Files:** Transcript file (tx_file.csv), which contains columns for: * —fov (Field Of View (FOV) where transcript is located) * —cell_ID (unique identifier of cell with a FOV; together, the “fov” and “cell_ID” columns are able to define a unique identifier for each cell in the entire sample. Note, transcripts without an assigned cell have a value of 0) * —x_global_px (see “x_local_px” description below; global position entails the relative transcript position within the large sample reference frame) * —y_global_px (as “x_global_px” but for y dimension) * —x_local_px (x position of transcript within FOV, measured in pixels. Note, to convert to microns, multiply pixel value by 0.18 um per pixel) * —y_local_px (same as “x_local_px” but for y dimension) * —target (HUGO gene symbol of target) * —CellComp (nuclear, membrane, or cytoplasmic of subcellular compartment where transcript was detected via cell segmentation algorithm; note, “0” denotes extracellular as mentioned above) Cell polygons file (polygons.csv), which contains simple polygon descriptions of cell boundaries in columns: * —fov (Field Of View [FOV] where transcript is located) * —cell_ID (unique identifier of cell with a FOV; together, the “fov” and “cell_ID” columns are able to define a unique identifier for each cell in the entire sample) * —x_local_px (x position within FOV, measured in pixels; note, to convert to microns, multiply pixel value by 0.18 um per pixel) * —y_local_px (same as “x_local_px” but for y dimension) * —x_global_px (relative x position of the ROV, measured in pixels. Note, to convert to microns, multiply pixel value by 0.18 um per pixel) * —y_global_px (as “x_global_px” but for y dimension) Cell expression file (exprMat_file.csv), which contains gene expression counts per cell per gene in columns: * —fov (Field Of View [FOV] where transcript is located) * —cell_ID (unique identifier of cell with a FOV; together, the “fov” and “cell_ID” columns are able to define a unique identifier for a cell in the entire sample; note, transcripts without an assigned cell have a value of 0) * —Alphabetical columns of genes targets (number of transcripts detected per gene target per cell) * —Columns of negative probes (probes that do not match any sequence within the transcriptome, which can can be used to assess background levels) Cell metadata file (metadata_file.csv), which contains metadata per cell in columns: * —fov (Field Of View [FOV] where transcript is located) * —cell_ID (unique identifier of cell with a FOV; together, the “fov” and “cell_ID” columns are able to define a unique identifier for each cell in the entire sample; note, transcripts without an assigned cell have a value of 0) * —Area (total pixels per given cell) * —Aspect ratio (width divided by height) * —CenterX_global_px (see “CenterX_local_px” description below; global positions describe the relative transcript position within the large sample reference frame) * —CenterY_global_px (as “CenterX_global_px” but for y dimension) * —CenterX_local_px (x position of transcript within the FOV in pixels; the pixel edge length is 180nm. Thus, to convert to microns multiply the pixel value by 0.18 um per pixel) * —CenterY_local_px (as “CenterX_local_px” but for y dimension) * —Width (maximum cell length in x dimension in pixels) * —Height (maximum cell length in y dimension in pixels) * —Mean.MembraneStain (mean fluorescence intensity of a given cell’s membrane stain i.e., CD298) * —Max.MembraneStain (max fluorescence intensity of a given cell’s membrane stain i.e., CD298) * —Mean.S100b.PMEL17 (mean fluorescence intensity of a given cell’s S100B/PMEL17 stain) * —Max.S100b.PMEL17 (max fluorescence intensity of a given cell’s S100B/PMEL17 stain) * —Mean.CD45 (mean fluorescence intensity of a given cell’s CD45 stain) * —Max.CD45 (max fluorescence intensity of a given cell’s CD45 stain) * —Mean.CD3 (mean fluorescence intensity of a given cell’s CD3 stain) * —Max.CD3 (max fluorescence intensity of a given cell’s CD3 stain) * —Mean.DAPI (mean fluorescence intensity of a given cell’s DAPI stain) * —Max.DAPI (max fluorescence intensity of a given cell’s DAPI stain) FOV Positions File (fov_positions_file.csv), which provides each FOV location within the total structure of the sample in columns: * —fov (Field Of View [FOV]) * —x_global_px (relative x position of FOV in pixels; yo convert to microns, multiply the pixel value by 0.18 um per pixel; NB, all FOVs are 5472 x 3648 pixels) * —y_global_px (as “x_global_px” but for y dimension) **Folders:** “CellOverlay”: Contains JPG images of each FOV showing cell boundaries from cell segmentation (shown as cyan lines) as well as DAPI stain in white. “CellComposite”: Contains JPG images of each FOV showing the immunofluorescence from the IHC markers and DAPI used in the SMI experiment "CompartmentLabels”: Contains TIF images that display the subcellular compartment definitions for each FOV determined during cell segmentation. Each compartment type is given a unique number and all pixels determined to be within that compartment type have an intensity value matching that number. “RawMorphologyImages”: Raw TIF image files for each FOV used for cell segmentation and to produce the cellComposite jPG images. “CellLabels”: TIF files for each FOV that displays the cell definitions determined during cell segmentation. Each cell identified is given a unique number (cell_ID) and all pixels determined to be within that cell have an intensity value matching that number. These cell_ID values are shared in the transcript, Cell Expression, and Cell Metadata files. A pixel not assigned to a cell has a “0” value. --- Other files contained in this upload include: * "processed_metadata_Slides_1-3.csv" and "processed_metadata_Slide_4.csv": These files contains processed data and cell-level analyses of Slides 1-3 and Slide 4, using the columns headers described in the “tx_file.csv”, “polygons.csv”, “exprMat_file.csv”, “metadata_file.csv”, “fov_positions_file.csv” files above. * FOVs for Slides 1-3.csv: Contains lesion descriptions of each FOV in Slides 1-3. * FOVs for Slide 4.csv: Contains lesion descriptions of each FOV in Slide 4. * InSituType package materials.zip: This self-contained .zip folder contains that InSituType package that utilized during the "Semi-supervised cell type annotation" data analysis; this package was available on GitHub @ [https://github.com/Nanostring-Biostats/InSituType/tree/main](https://github.com/Nanostring-Biostats/InSituType/tree/main) as of April 10th 2024. --- ## Code/Software Files are compatible with open-source packages such as Seurat in R or Squidpy in Python. More information about how to employ these open-source packages can be found at: Seurat: [https://satijalab.org/seurat/](https://satijalab.org/seurat/) Squidpy: [https://squidpy.readthedocs.io/en/stable/notebooks/tutorials/tutorial\\_nanostring.html](https://squidpy.readthedocs.io/en/stable/notebooks/tutorials/tutorial\\_nanostring.html)