WTX Pancreas README

1 Introduction

FFPE Pancreas sample run on the CosMx^® Spatial Molecular Imager using a development version of the CosMx Whole Transcriptome (WTX) panel.

Table 1.1

Metric	Pancreas
Number of FOVs	266
Total Tissue Area (mm²)	69.73
Mean Single Cell Size (um²)	71.99
Number of Cells In Analysis	413373
Total Transcripts Assigned To Cells	565662729
Mean Transcripts Per Cell	1368.41
Maxium Transcripts Per Cell	8121
Mean Unique Genes Per Cell	603.96
Mean Transcripts Per um²	19.01
Mean Negative Counts Per Cell	0.35
Mean Negative per Plex per Cell	0.01
Mean False Codes per Plex per Cell	0.01
Signal-to-Noise Ratio (global)	10.39
Signal-to-Noise Ratio Total (global)	4.94
Genes Above LOD	8726
Percent Transcripts Assigned to Cells	89.62

2 Flat File Descriptions

2.1 Transcript Coordinates

fov	cell_ID	cell	x_local_px	y_local_px	x_global_px	y_global_px	z	target	CellComp
1	0	c_1_1_0	4255	1422	61845	79442	7	DDC	NA
1	0	c_1_1_0	4255	1423	61846	79441	8	DDC	NA
1	0	c_1_1_0	4255	3592	61845	77272	7	SAA1	NA
1	0	c_1_1_0	4255	3716	61846	77148	5	CARHSP1	NA
1	0	c_1_1_0	4255	3716	61845	77148	6	CARHSP1	NA
1	0	c_1_1_0	4254	2157	61844	78707	3	ATOH7	NA

Description of the baseline transcripts file format for AtoMx^® Spatial Informatics Platrform (SIP) 3.10.5.

Column Name	Type	Description
fov	Int	The field of view (FOV) number.
cell_ID	Int	Unique identifier for a single cell within a given FOV. To make a unique identifier for a cell within the whole sample use both the fov and cell_ID columns.
cell	string	A study-wide unique cell identifier. Combination of c(ell), slide ID, fov, and cell_ID. Note that this is equivalent to cell_ID in napari-cosmx.
x_local_px	float	The x position (in pixels) relative to the given FOV.
y_local_px	float	The y position (in pixels) relative to the given FOV.
x_global_px	float	The x position (in pixels) relative to the tissue.
y_global_px	float	The y position (in pixels) relative to the tissue.
z	Int	The z plane.
target	string	The name of the target.
CellComp	string	Subcellular location of target.

2.2 Cell Expression

Description of the baseline expression matrix file format for AtoMx SIP 3.10.5.

Column Name	Type	Description
fov	Int	The field of view (FOV) number.
cell_ID	Int	Unique identifier for a single cell within a given FOV. To make a unique identifier for a cell within the whole sample use both the fov and cell_ID columns. All transcripts not assigned to a cell are show with a cell_ID value of 0.
(Gene expression target)	Int	The number of transcripts observed for a given gene target for a given cell.
(Negative Probe, e.g., Negative1)	Int	Negative probes, which do not match any sequence within the transcriptome or genome. These can be used to assess background levels.
(System Control)	Int	System Control codes are codes which do not have any physical probe associated with them.

2.3 Cell Metadata

Description of the baseline metadata file format for AtoMx SIP 3.10.5.

Column Name	Type	Description
fov	Int	The field of view (FOV) number.
Area	Int	Number of pixels assigned to a given cell.
AspectRatio	float	Width divided by height.
Width	Int	Cell’s maximum length in x dimension (pixels).
Height	Int	Cell’s maximum length in y dimension (pixels).
Mean.(IF)	Int	The mean fluorescence intensity for a given cell.
Max.(IF)	Int	The max fluorescence intensity for a given cell.
SplitRatioToLocal	float	If cell abuts the FOV border: the ratio of Area to mean cell area for that FOV. If cell does not border the FOV boundary: 0.
NucArea	Int	Number of pixels assigned to a given nucleus.
NucAspectRatio	float	Width divided by height of nucleus.
Circularity	float	Area to perimeter ratio. 1 = circle; < 1 less circular (Fu et al. 2024).
Eccentricity	float	A cell’s minor axis divided by its major axis (Fu et al. 2024).
Perimeter	Int	The perimeter of the cell (in pixels).
Solidity	float	The Area of the cell divided by its convex area. A measure of the “density” of a cell with values < 1 indicating increased cell irregularity (Fu et al. 2024).
cell_id	string	A study-wide unique cell identifier. Combination of c(ell), slide_ID, fov, and cell_ID. Note that this is equivalent to cell_ID in napari-cosmx.
version	string	The version of the target decoding used.
dualfiles	string	(Invariable constant)
Run_name	string	(Invariable constant)
Run_Tissue_name	string	The name of the slide.
ISH.concentration	string	Concentration
Dash	string	(Invariable constant)
tissue	string	(Invariable constant)
Panel	string	Experimental Panel
assay_type	string	Assay type
slide_ID	Int	Unique identifier for the slide
cell_ID	Int	Unique identifier for a single cell within a given FOV. To make a unique identifier for a cell within the whole sample use both the fov and cell_ID columns.
unassignedTranscripts	float	Proportion of transcripts in the FOV the cell resides in that are not assigned within any cell. This value is an FOV-level metric that is repeated for each cell (excluding cell 0).
median_RNA	Int	FOV-level statistic. Median RNA target probe expression across all cells within a given FOV.
RNA_quantile_(proportion)	float	FOV-level statistic. The (proportion*100) percentile of RNA target expression across all cells within a given FOV.
nCount_RNA	Int	Total RNA transcripts observed.
nFeature_RNA	Int	Total number of unique RNA transcripts observed.
median_negprobes	Int	FOV-level statistic. Median negative probe expression across all cells within a given FOV.
negprobes_quantile_(proportion)	float	FOV-level statistic. The (proportion*100) percentile of negative probe expression across all cells within a given FOV.
nCount_negprobes	Int	Total Negative Control Probe counts observed.
nFeature_negprobes	Int	Total number of unique Negative Control Probe counts observed.
median_falsecode	Int	FOV-level statistic. Median System Control counts across all cells within a given FOV.
falsecode_quantile_(proportion)	float	FOV-level statistic. The (proportion*100) percentile of System Control counts across all cells within a given FOV.
nCount_falsecode	Int	Total System Control codes counts observed. These codes do not have a physical probe in the experiment.
nFeature_falsecode	Int	Total number of unique System Control codes counts observed.
Area.um2	float	The cell area in units of \(\mu m^{2}\).
CenterX_local_px	Int	The x position of this cell within the FOV, measured in pixels. The pixel edge length is 120 nm. Thus, to convert to microns multiply the pixel value by 0.12028 \(\mu\)m per pixel.
CenterY_local_px	Int	Same as CenterX_local_px but for the y dimension.
CenterX_global_px	float	See CenterX_local_px description. The global positions describes the relative position of this cell within the large sample reference frame.
CenterY_global_px	float	Same as CenterX_global_px but for the y dimension.
cell	string	Redundant with cell_id.

2.4 FOV Positions

Description of the baseline FOV file format for AtoMx SIP 3.10.5.

Column Name	Type	Description
FOV	Int	The field of view (FOV) number.
x_global_px	Int	The x location (in pixels) of the FOV relative to other FOVs.
y_global_px	Int	The y location (in pixels) of the FOV relative to other FOVs.
x_global_mm	float	The x location (in millimeters) of the FOV relative to other FOVs.
y_global_mm	float	The y location (in millimeters) of the FOV relative to other FOVs.

2.5 Polygons

Column Name	Type	Description
fov	Int	The field of view (FOV) number.
cellID	Int	Unique identifier for a single cell within a given FOV. To make a unique identifier for a cell within the whole sample use both the fov and cell_ID columns.
cell	string	A study-wide unique cell identifier. Combination of c(ell), slide ID, and cell_ID. Note that this is equivalent to cell_ID in napari-cosmx.
x_local_px	Int	The x position (in pixels) of vertex relative to the given FOV.
y_local_px	Int	The y position (in pixels) of vertex relative to the given FOV.
x_global_px	Int	The x position (in pixels) of vertex relative to the tissue.
y_global_px	Int	The y position (in pixels) of vertex relative to the tissue.

References

Fu, Xiaohang, Yingxin Lin, David M. Lin, Daniel Mechtersheimer, Chuhan Wang, Farhan Ameen, Shila Ghazanfar, Ellis Patrick, Jinman Kim, and Jean Y. H. Yang. 2024. “BIDCell: Biologically-Informed Self-Supervised Learning for Segmentation of Subcellular Spatial Transcriptomics Data.” Nature Communications 15 (January): 509. https://doi.org/10.1038/s41467-023-44560-w.