Kayla C. Jackson

The paper develops a model to distinguish biological from technical spatial variability in spatial transcriptomics data and introduces the stipple software for analysis.

This paper introduces concordex, a method to identify spatially homogeneous regions in tissues by decomposing gene expression patterns into cell-type and spatial variation, demonstrating its effectiveness across datasets.

This paper extends contrastive PCA by introducing spatial and functional variants, applying them to analyze gene expression in cancer and immune response to vaccination.

This study compares Seurat and Scanpy, finding significant differences in their scRNA-seq analysis outputs, comparable to low sequencing depth or cell coverage.

This paper introduces rho PCA, a method that improves upon contrastive PCA by approximating the Rayleigh quotient, offering better accuracy and efficiency for dimension reduction in genomics data.

Geospatial exploratory statistics, including local, bivariate and multivariate spatial methods, are packaged for spatial omics behind one interface, with matched R/Bioconductor and Python implementations.