转录组
电池类型
细胞
计算生物学
核糖核酸
基因表达
生物
仿形(计算机编程)
基因表达谱
基因
遗传学
计算机科学
操作系统
作者
Chloé B. Steen,Chih Long Liu,Ash A. Alizadeh,Aaron M. Newman
标识
DOI:10.1007/978-1-0716-0301-7_7
摘要
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.
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