Beautiful work from @steglelab.bsky.social and @danaivagiaki.bsky.social!

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...

From great collaborations come great things. Excited to share Segger, the solution to segmentation of spatial transcriptomics (ST) data, with the @steglelab.bsky.social and @moritzgerstung.bsky.social labs, spearheaded by the great Andrew Moorman and Elyas Heidari www.biorxiv.org/content/10.1...

Segger logo

Message passing intuition behind the segger’s link-prediction model and the network architecture

1/ New preprint! 🍳

@elihei.bsky.social and our team at @embl.org , @dkfz.bsky.social, and @mskcancercenter.bsky.social built #segger - a fast, accurate cell segmentation tool for spatial transcriptomics that assigns transcripts to their cell origins!

doi.org/10.1101/2025...

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...

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...

Spatial transcriptomics holds great promise to understand biological tissue function, but the assignment of transcripts to cells has been a substantial bottleneck.

For this reason, Elyas Heidari, a student in my lab and in @steglelab.bsky.social built segger.

www.biorxiv.org/content/10.1...