Single-cell entropy for accurate estimation of differentiation potency from a cell’s transcriptome
Robust quantification of the differentiation potential of single cells is a task of great importance. Here the authors integrate single-cell RNA-Seq profiles with a cellular interaction network to compute the signaling entropy, and show that it can identify normal and cancer stem-cell phenotypes.
Saved in:
Main Authors: | Andrew E. Teschendorff, Tariq Enver |
---|---|
Format: | article |
Language: | EN |
Published: |
Nature Portfolio
2017
|
Subjects: | |
Online Access: | https://doaj.org/article/2b700eada7d045eeb538e7f30e6e4773 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Accurate estimation of cell composition in bulk expression through robust integration of single-cell information
by: Brandon Jew, et al.
Published: (2020) -
Publisher Correction: Accurate estimation of cell composition in bulk expression through robust integration of single-cell information
by: Brandon Jew, et al.
Published: (2020) -
Accurate estimation of cell-type composition from gene expression data
by: Daphne Tsoucas, et al.
Published: (2019) -
Dynamics of lineage commitment revealed by single-cell transcriptomics of differentiating embryonic stem cells
by: Stefan Semrau, et al.
Published: (2017) -
Transcriptomic entropy benchmarks stem cell-derived cardiomyocyte maturation against endogenous tissue at single cell level.
by: Suraj Kannan, et al.
Published: (2021)