Dimension Reduction by Spatial Components Analysis Improves Pattern Detection in Multivariate Spatial Data
Niklas Kleinenkuhnen, David Köhler, Till Baar, Chrysa Nikopoulou, Vangelis Kondylis, Matthias C. Schmid, Peter Tessarz, Achim Tresch
The paper introduces SPACO, a method for dimension reduction in spatial transcriptomics data that improves pattern detection by maximizing Moran's I and outperforms PCA.
bioRxiv · Oct 12, 2023 · PreprintBioinformatics