.png){kind=icon}
Return
Single-cell colocalization analysis using a deep generative model
.png){kind=icon}
OA
AI
DOI：10.1016/j.cels.2024.01.007.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Analyzing colocalization of single cells with heterogeneous molecular phenotypes is essential for understanding cell -cell interactions, and cellular responses to external stimuli and their biological functions in diseases and tissues. However, existing computational methodologies identified the colocalization patterns between predefined cell populations, which can obscure the molecular signatures arising from intercellular communication. Here, we introduce DeepCOLOR, a computational framework based on a deep generative model that recovers intercellular colocalization networks with single -cell resolution by the integration of single -cell and spatial transcriptomes. Along with colocalized population detection accuracy that is superior to existing methods in simulated dataset, DeepCOLOR identified plausible cell -cell interaction candidates between colocalized single cells and segregated cell populations defined by the colocalization relationships in mouse brain tissues, human squamous cell carcinoma samples, and human lung tissues infected with SARSCoV-2. DeepCOLOR is applicable to studying cell -cell interactions behind various spatial niches. A record of this paper's transparent peer review process is included in the supplemental information.
Keywords:
SERUM-LEVELS
EXPRESSION
COMMUNICATION
CANCER
TARGET
CXCL9
RNA
SEQ
Journal
IF:
7.7
Papers:
1.4K
Citations:
1.2W
Organization
View more organizations
Cited Papers
MMP14 in Sarcoma: A Regulator of Tumor Microenvironment Communication in Connective Tissues.png)
CELLS
OAAI
CELLSIF5.2
OAAIShareSaveHigh-throughput sequencing of the transcriptome and chromatin accessibility in the same cellNATURE BIOTECHNOLOGYOAAI
NATURE BIOTECHNOLOGYIF41.7
OAAIShareSaveCellPhoneDB: inferring cell-cell communication from combined expression of multi-subunit ligand-receptor complexesNATURE PROTOCOLSOAAI
NATURE PROTOCOLSIF16
OAAIShareSaveShareSaveHigh-resolution alignment of single-cell and spatial transcriptomes with CytoSPACENATURE BIOTECHNOLOGYOAAI
NATURE BIOTECHNOLOGYIF41.7
OAAIShareSaveIntegration of spatial and single-cell transcriptomic data elucidates mouse organogenesisNATURE BIOTECHNOLOGYOAAI
NATURE BIOTECHNOLOGYIF41.7
OAAIShareSaveAnalysis of Single-Cell RNA-Seq Identifies Cell-Cell Communication Associated with Tumor CharacteristicsCELL REPORTSOAAI
CELL REPORTSIF6.9
OAAIShareSave View more