| Literature DB >> 31960376 |
Chloé B Steen1, Chih Long Liu1,2, Ash A Alizadeh3,4,5,6, Aaron M Newman7,8.
Abstract
CIBERSORTx is a suite of machine learning tools for the assessment of cellular abundance and cell type-specific gene expression patterns from bulk tissue transcriptome profiles. With this framework, single-cell or bulk-sorted RNA sequencing data can be used to learn molecular signatures of distinct cell types from a small collection of biospecimens. These signatures can then be repeatedly applied to characterize cellular heterogeneity from bulk tissue transcriptomes without physical cell isolation. In this chapter, we provide a detailed primer on CIBERSORTx and demonstrate its capabilities for high-throughput profiling of cell types and cellular states in normal and neoplastic tissues.Entities:
Keywords: Cellular heterogeneity; Deconvolution; Digital cytometry; Gene expression; Tumor microenvironment; scRNA-seq
Mesh:
Year: 2020 PMID: 31960376 PMCID: PMC7695353 DOI: 10.1007/978-1-0716-0301-7_7
Source DB: PubMed Journal: Methods Mol Biol ISSN: 1064-3745