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论文题目: Single-cell entropy for accurate estimation of differentiation potency from a cell's transcriptome
英文论文题目: Single-cell entropy for accurate estimation of differentiation potency from a cell's transcriptome
第一作者: Teschendorff, AE; Enver, T
英文第一作者: Teschendorff, AE; Enver, T
联系作者: Teschendorff, AE (reprint author), Shanghai Inst Biol Sci, CAS MPG Partner Inst Computat Biol, CAS Key Lab Computat Biol, 320 Yue Yang Rd, Shanghai 200031, Peoples R China.
英文联系作者: Teschendorff, AE (reprint author), Shanghai Inst Biol Sci, CAS MPG Partner Inst Computat Biol, CAS Key Lab Computat Biol, 320 Yue Yang Rd, Shanghai 200031, Peoples R China.
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发表年度: 2017
卷: 8
期:
页码: 15599
摘要: The ability to quantify differentiation potential of single cells is a task of critical importance. Here we demonstrate, using over 7,000 single-cell RNA-Seq profiles, that differentiation potency of a single cell can be approximated by computing the signalling promiscuity, or entropy, of a cell's transcriptome in the context of an interaction network, without the need for feature selection. We show that signalling entropy provides a more accurate and robust potency estimate than other entropy-based measures, driven in part by a subtle positive correlation between the transcriptome and connectome. Signalling entropy identifies known cell subpopulations of varying potency and drug resistant cancer stem-cell phenotypes, including those derived from circulating tumour cells. It further reveals that expression heterogeneity within single-cell populations is regulated. In summary, signalling entropy allows in silico estimation of the differentiation potency and plasticity of single cells and bulk samples, providing a means to identify normal and cancer stem-cell phenotypes.
英文摘要: The ability to quantify differentiation potential of single cells is a task of critical importance. Here we demonstrate, using over 7,000 single-cell RNA-Seq profiles, that differentiation potency of a single cell can be approximated by computing the signalling promiscuity, or entropy, of a cell's transcriptome in the context of an interaction network, without the need for feature selection. We show that signalling entropy provides a more accurate and robust potency estimate than other entropy-based measures, driven in part by a subtle positive correlation between the transcriptome and connectome. Signalling entropy identifies known cell subpopulations of varying potency and drug resistant cancer stem-cell phenotypes, including those derived from circulating tumour cells. It further reveals that expression heterogeneity within single-cell populations is regulated. In summary, signalling entropy allows in silico estimation of the differentiation potency and plasticity of single cells and bulk samples, providing a means to identify normal and cancer stem-cell phenotypes.
刊物名称: NATURE COMMUNICATIONS
英文刊物名称: NATURE COMMUNICATIONS
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学科: Multidisciplinary Sciences
英文学科: Multidisciplinary Sciences
影响因子: 12.124
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论文类别: Article
英文论文类别: Article
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