Profiling Cell Type Abundance and Expression in Bulk Tissues with CIBERSORTx.
Profiling Cell Type Abundance and Expression in Bulk Tissues with CIBERSORTx.
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DOI：
10.1007/978-1-0716-0301-7_7
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发表时间：
2020
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影响因子：
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通讯作者：
Newman AM
中科院分区：
文献类型：
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作者：
Steen CB;Liu CL;Alizadeh AA;Newman AM
CIBERSORTx是一套机器学习工具，用于从大量组织转录组图谱中评估细胞丰度和细胞类型特异性基因表达模式。有了这个框架，单细胞或批量分选的RNA测序数据可用于从少量生物标本中了解不同细胞类型的分子特征。然后可以重复应用这些特征来表征来自大量组织转录组的细胞异质性，而无需物理细胞分离。在本章中，我们提供了一个详细的引物CIBERSORTx和展示其功能的高通量分析的细胞类型和细胞状态在正常和肿瘤组织。
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.