{"id":"doi:10.1038/ncomms15599","kind":"article","title":"Single-cell entropy for accurate estimation of differentiation potency from a cell's transcriptome","authors":["Teschendorff AE","Enver T"],"author_count":2,"year":2017,"published":"2017-06-01","venue":"Nature communications","cited_by":279,"doi":"10.1038/ncomms15599","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1038/ncomms15599","archive_url":"https://space-kitty.com/papers/doi:10.1038/ncomms15599","updated":null,"pmid":"28569836","pmcid":"PMC5461595","openalex_id":null,"pdf_url":"https://europepmc.org/articles/PMC5461595/pdf","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_license":"CC-BY (article license as recorded by Europe PMC; abstract reproduced unmodified apart from markup removal)","license":"CC-BY","is_open_access":true,"retracted":false,"peer_reviewed":null,"categories":[],"details":null,"provenance":"europepmc","attribution":"Abstract of \"Single-cell entropy for accurate estimation of differentiation potency from a cell's transcriptome\" by Teschendorff AE, Enver T, https://doi.org/10.1038/ncomms15599, used under its Creative Commons Attribution license (CC-BY); markup removed, otherwise unmodified.","topics":[{"slug":"connectomics","name":"Connectomics & Brain Mapping","domain_slug":"neuroscience"}],"cited_in_dossiers":[]}