Background

Multiplexed imaging technologies are amongst the fastest growing areas of multi-omics. These technologies capture many parameters of single cells while preserving their spatial location. As such, there is a need for a flexible, robust, and easily deployed end to end computational pipeline for processing and analysis of the data such technologies produce. The goal of such a pipeline is to capture cell-type compositions in a localized shape-preserving manner. To help researchers achieve this goal, we have developed Hudson.

Fluorescent Imaging is the visualization of fluorescent dyes or proteins as labels for molecular processes or structures. It enables a wide range of experimental observations including the location and dynamics of gene expression, protein expression and molecular interactions in cells and tissues.

Given the computationally intense and programmatically advanced nature of analyzing highly multiplexed images, Hudson saves significant time for researchers wanting to incorporate spatial information and serves the overarching goal of making spatial analysis more accessible.