scQUEST: Quantifying tumor ecosystem heterogeneity from mass or flow cytometry data

Abstract

With mass and flow cytometry, millions of single-cell profiles with dozens of parameters can be measured to comprehensively characterize complex tumor ecosystems. Here, we present scQUEST, an open-source Python library for cell type identification and quantification of tumor ecosystem heterogeneity in patient cohorts. We provide a step-by-step protocol on the application of scQUEST on our previously generated human breast cancer single-cell atlas using mass cytometry and discuss how it can be adapted and extended for other datasets and analyses.