ovrl.py

ovrlpy identifies overlapping cells, tissue folds, and inaccurate cell segmentation by analyzing transcript localization in three dimensions.

Key Features:

• 3D overlap detection: Identifies spatial doublets in the vertical dimension that result in segmented cells containing transcripts originating from multiple cell types.
• Cell segmentation quality assessment: Detects inaccurate cell segmentation in imaging-based spatially resolved transcriptomics data.
• Tissue fold detection: Identifies tissue folds that may confound transcript-to-cell assignment.

Scientific Applications:

• Spatial transcriptomics quality control: Evaluates cell segmentation accuracy in imaging-based spatially resolved transcriptomics where two-dimensional segmentation is applied to three-dimensional transcript data.
• Vertical signal integrity analysis: Assesses whether transcripts within segmented cells truly originate from single cell types or from multiple cells overlapping in the z-dimension.

Methodology:

Analyzes transcript localization in three dimensions to identify overlapping cells, tissue folds, and inaccurate cell segmentation.