Characterization of cell-fate decision landscapes by estimating transcription factor dynamics.
RNA velocity
cell-fate modeling
differentiation
endocrine cell
gene regulation
Journal
Cell reports methods
ISSN: 2667-2375
Titre abrégé: Cell Rep Methods
Pays: United States
ID NLM: 9918227360606676
Informations de publication
Date de publication:
24 07 2023
24 07 2023
Historique:
received:
06
09
2022
revised:
23
03
2023
accepted:
01
06
2023
medline:
4
8
2023
pubmed:
3
8
2023
entrez:
3
8
2023
Statut:
epublish
Résumé
Time-specific modulation of gene expression during differentiation by transcription factors promotes cell diversity. However, estimating their dynamic regulatory activity at the single-cell level and in a high-throughput manner remains challenging. We present FateCompass, an integrative approach that utilizes single-cell transcriptomics data to identify lineage-specific transcription factors throughout differentiation. By combining a probabilistic framework with RNA velocities or differentiation potential, we estimate transition probabilities, while a linear model of gene regulation is employed to compute transcription factor activities. Considering dynamic changes and correlations of expression and activities, FateCompass identifies lineage-specific regulators. Our validation using
Identifiants
pubmed: 37533652
doi: 10.1016/j.crmeth.2023.100512
pii: S2667-2375(23)00141-8
pmc: PMC10391345
doi:
Substances chimiques
Transcription Factors
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
100512Informations de copyright
© 2023 The Author(s).
Déclaration de conflit d'intérêts
The authors declare no competing interests.
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