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Wang, W. ; Wang, Y.* ; Lyu, R.* ; Grün, D.*

Scalable identification of lineage-specific gene regulatory networks from metacells with NetID.

Genome Biol. 25:275 (2024)
Verlagsversion DOI PMC
Open Access Gold
Creative Commons Lizenzvertrag
The identification of gene regulatory networks (GRNs) is crucial for understanding cellular differentiation. Single-cell RNA sequencing data encode gene-level covariations at high resolution, yet data sparsity and high dimensionality hamper accurate and scalable GRN reconstruction. To overcome these challenges, we introduce NetID leveraging homogenous metacells while avoiding spurious gene-gene correlations. Benchmarking demonstrates superior performance of NetID compared to imputation-based methods. By incorporating cell fate probability information, NetID facilitates the prediction of lineage-specific GRNs and recovers known network motifs governing bone marrow hematopoiesis, making it a powerful toolkit for deciphering gene regulatory control of cellular differentiation from large-scale single-cell transcriptome data.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Korrespondenzautor
Schlagwörter Transcription Factors; C/ebp-alpha; Cell; Mechanisms; Expression; Database; Gata-1; Klf1
ISSN (print) / ISBN 1474-760X
e-ISSN 1465-6906
Zeitschrift Genome Biology
Quellenangaben Band: 25, Heft: 1, Seiten: , Artikelnummer: 275 Supplement: ,
Verlag BioMed Central
Verlagsort Campus, 4 Crinan St, London N1 9xw, England
Nichtpatentliteratur Publikationen
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Computational Biology (ICB)
Förderungen Julius-Maximilians-Universitt Wrzburg (3088)