# Single-cell entropy for accurate estimation of differentiation potency from a cell's transcriptome

Article · Teschendorff AE, Enver T

- Archive id: doi:10.1038/ncomms15599
- Published: 2017-06-01
- Venue: Nature communications
- DOI: https://doi.org/10.1038/ncomms15599
- PMID: 28569836
- PMCID: PMC5461595
- Citations: 279
- Source URL: https://doi.org/10.1038/ncomms15599
- PDF: https://europepmc.org/articles/PMC5461595/pdf
- Provenance: europepmc

## Abstract

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.

_Abstract reproduced under CC-BY (article license as recorded by Europe PMC; abstract reproduced unmodified apart from markup removal)._

Topics: [Connectomics & Brain Mapping](https://space-kitty.com/topics/connectomics)

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