Anna Christina Schaar

InterScale models both local and global cellular interactions in spatial transcriptomics data, revealing spatially restricted differentiation programs and disease-associated tissue remodeling.

This paper benchmarks the Ultima UG100 and Illumina NovaSeq platforms on FFPE tissues for various sequencing modalities, finding they produce comparable results with subtle discrepancies in non-coding transcripts.

Spapros selects optimal probe sets for targeted spatial transcriptomics to improve cell type identification and spatial variation detection across multiple datasets.

GraphCompass provides graph analysis methods to compare cell spatial organization across conditions using spatial omics data.

Pretrained on 57 million dissociated and 53 million spatial human and mouse cells, a 49.3M-parameter transformer predicts niche, region, neighborhood composition and density, and carries spatial labels onto scRNA-seq.

Squidpy extends Scanpy/AnnData with spatial neighbor graphs and a lazy-loading image container, enabling spatial statistics, ligand-receptor tests, image features, and ~10-fold faster neighborhood enrichment than Giotto.

The paper introduces NCEM, a graph neural network method for modeling cell communication in spatial molecular profiling data, identifying niche-dependent gene expression and cell state variation across multiple tissues.