Journal
NATURE COMMUNICATIONS
Volume 8, Issue -, Pages -Publisher
NATURE PUBLISHING GROUP
DOI: 10.1038/ncomms15599
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Funding
- NSFC (National Science Foundation of China)
- Royal Society Newton Advanced Fellowship (NAF) [31571359, 31401120, 522438, 164914]
- Medical Research Council [519159]
- Cancer Research UK [12796] Funding Source: researchfish
- Great Ormond Street Hospital Childrens Charity [W1062] Funding Source: researchfish
- Gynaecology Research Fund (The Eve Appeal) [537067] Funding Source: researchfish
- Medical Research Council [MR/M009033/1, MC_U137973817, MR/N000838/1] Funding Source: researchfish
- MRC [MR/M009033/1, MC_U137973817, MR/N000838/1] Funding Source: UKRI
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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.
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