Weighted sliced inverse regression for scalable supervised dimensionality reduction of spatial transcriptomics data
Maximilian Woollard, Pratibha Panwar, Luke T. G. Harland, Jeremy Mo, Hanyun Zhang, Alexander Swarbrick, Berthold Göttgens, Shila Ghazanfar, Linh H. Nghiem
This paper introduces wSIR, a scalable supervised dimensionality reduction method for spatial transcriptomics data, which retains predictive power of spatial coordinates and is demonstrated on breast cancer and embryonic development datasets.
Nature Communications · Sep 3, 2026Peer-reviewedGenomics