Notice: Users may be experiencing issues with displaying some pages on stanfordhealthcare.org. We are working closely with our technical teams to resolve the issue as quickly as possible. Thank you for your patience.
 

Learn about the flu shot, COVID-19 vaccine, and our masking policy »

Stanford Health Care

Profiling Cellular Ecosystems at Single-Cell Resolution and at Scale with EcoTyper. Methods in molecular biology (Clifton, N.J.) Steen, C. B., Luca, B. A., Alizadeh, A. A., Gentles, A. J., Newman, A. M. 2023; 2629: 43-71

Abstract

Tissues are composed of diverse cell types and cellular states that organize into distinct ecosystems with specialized functions. EcoTyper is a collection of machine learning tools for the large-scale delineation of cellular ecosystems and their constituent cell states from bulk, single-cell, and spatially resolved gene expression data. In this chapter, we provide a primer on EcoTyper and demonstrate its use for the discovery and recovery of cell states and ecosystems from healthy and diseased tissue specimens.

View details for DOI 10.1007/978-1-0716-2986-4_4

View details for PubMedID 36929073

View details for PubMedCentralID 9067608