Nate Osher

Biostatistics PhD Candidate

University of Michigan

Personal Background

I am a PhD candidate in the University of Michigan department of Biostatistics. My advisors are Dr. Veera Baladandayuthapani and Dr. Jian Kang. My research primarily involves Bayesian modeling of of spatial cancer pathology imaging data. Among other things, this includes modeling point process data, developing Bayesian selection priors, and functional data analysis.

Publications & Software

Nathaniel Osher, Jian Kang, Arvind Rao, Veerabhadran Baladandayuthapani

Spatially Structured Regression for Non-conformable Spaces: Integrating Pathology Imaging and Genomics Data in Cancer

The goal of this project was to develop a method to model the variability in tumor-immune interaction both within and between tumor biopsies with respect to biopsy level gene expression data. This is challenging due to the non-conformability of the tumor biopsies.

Paper

Code

Maria Masotti, Nathaniel Osher, Joel Eliason, Arvind Rao, Veera Baladandayuthapani

DIMPLE: An R package to quantify, visualize, and model spatial cellular interactions from multiplex imaging with distance matrices

The goal of this project was to develop a software package to analyze interaction between cells of different types in multiplex imaging data in a scalable, computationally efficient manner.

Paper

Code

Nathaniel Osher, Jian Kang, Santhoshi Krishnan, Arvind Rao, Veera Baladandayuthapani

SPARTIN: a Bayesian method for the quantification and characterization of cell type interactions in spatial pathology data

The goal of this project was to develop methods to quantify interaction (i.e. co-localization) between tumor cells and immune cells in melanoma imaging data.

Paper

Code