Lauren Cole Peres

The paper introduces multiScaleAC, a method to analyze cell-cell interactions across spatial scales using a modified Moran's I with varying kernel bandwidths, showing improved statistical power and reduced bias.

The paper develops a functional data analysis framework to model spatial clustering in ovarian cancer, identifying prognostic T cell patterns beyond immune cell abundance.

This study shows HGSC transcriptomic subtypes are driven by tumor cellular composition rather than intrinsic biology, with high predictive accuracy using deconvolution methods.

The paper deconvolves adipocyte proportions from bulk RNA-seq data of HGSOC tumors and finds higher adipocyte content is associated with worse survival.

The paper provides exact analytical solutions for the mean and variance of the Nearest Neighbor G(r) spatial metric under complete spatial randomness, avoiding computationally expensive permutations.