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Identifying 3D signal overlaps in spatial transcriptomics data with ovrlpy
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AI
DOI：10.1038/s41587-026-03004-8.png)
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Abstract
En 中文
Imaging-based spatially resolved transcriptomics can localize transcripts within tissue sections in three dimensions. However, cell segmentation, which assigns transcripts to cells, is usually performed in two dimensions and spatial doublets in the vertical dimension result in segmented cells containing transcripts originating from multiple cell types. Here we present a computational tool called ovrlpy that identifies overlapping cells, tissue folds and inaccurate cell segmentation by analyzing transcript localization in three dimensions. Ovrlpy identifies overlapping cell signals in the vertical dimension of spatial transcriptomics data.
Keywords:
Gene expression
Software
Transcriptomics
Life Sciences
general
Biotechnology
Biomedicine
Agriculture
Biomedical Engineering/Biotechnology
Bioinformatics
Journal
IF:
41.7
Papers:
1.2W
Citations:
10.1W
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