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Accurate cell segmentation remains a major issue for spatial transcriptomics. Elyas Heidari and colleagues from the Gerstung, Pe'er and Stegle Labs released Segger, a new algorithm that uses GNN to model both transcripts and cells. More details in their preprint: www.biorxiv.org/content/10.1...

Segger: Fast and accurate cell segmentation of imaging-based spatial transcriptomics data

The accurate assignment of transcripts to their cells of origin remains the Achilles heel of imaging-based spatial transcriptomics, despite being critical for nearly all downstream analyses. Current c...

biorxiv.org