qupath-spot-utils

Scripts for processing microarray spots in QuPath

Citation

If you use this package in your work, please cite:

Geras, A., Darvish Shafighi, S., Domżał, K. et al. Celloscope: a probabilistic model for marker-gene-driven cell type deconvolution in spatial transcriptomics data. Genome Biol 24, 120 (2023). https://doi.org/10.1186/s13059-023-02951-8

extract_annotated_spots

This script finds spots that intersect annotated regions within a slide and saves their positions + annotated labels in a CSV file.

Input format:

Spot coordinates file:

ACGCCTGACACGCGCT-1,0,0,0,947,1161
TACCGATCCAACACTT-1,0,1,1,1099,1248
...
ATACCCTGGCTCAAAT-1,0,1,13,1101,2295
GGGTTTCCGGCTTCCA-1,0,0,14,950,2383

Scale factor file:

{"spot_diameter_fullres": 113.41830135687084, "tissue_hires_scalef": 0.1370614, "fiducial_diameter_fullres": 183.2141791149452, "tissue_lowres_scalef": 0.04111842}

Usage:

1. Load an annotated tissue slide in QuPath
2. Click Automate -> Show script editor in QuPath's menu
3. In the Script Editor window, click File -> Open... and choose the extract_annotated_spots.groovy file
4. Navigate to the bottom of the file and fill in the proper file paths for SPOT_COORDINATES_FILE_PATH, SCALE_FACTOR_FILE_PATH and OUTPUT_FILE_PATH
5. Click Run -> Run in the Script Editor window

cell_detection

This script counts the cells for each provided spot coordinate.

Input format: Spot coordinates file:

0x0,947,1161
0x1,1099,1248
...
10x10,1101,2295
10x11,950,2383

Usage:

1. Load a tissue slide in QuPath
2. Click Automate -> Show script editor in QuPath's menu
3. In the Script Editor window, click File -> Open... and choose the cell_detection.groovy file
4. Replace PATH_TO_COORDINATES_FILE with the path to the corresponding spot coordinates file and PATH_TO_OUTPUT_FILE with your desired out output file path
5. Click Run -> Run in the Script Editor window