Cell annotation using scRNA-seq data: a protein-protein interaction network approach

Pathway analysis is an important step in the interpretation of single cell transcriptomic data, as it provides powerful information to detect which cellular processes are active in each individual cell. We have recently developed a protein-protein interaction network-based framework to quantify plur...

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Detalles Bibliográficos
Autores: Senra, Daniela, Guisoni, Nara Cristina, Diambra, Luis Aníbal
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2023
País:Argentina
Institución:Universidad Nacional de La Plata
Repositorio:SEDICI (UNLP)
Idioma:inglés
OAI Identifier:oai:sedici.unlp.edu.ar:10915/160415
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/160415
Access Level:acceso abierto
Palabra clave:Biología
scRNA-seq
Protein-protein interaction networks
Cell annotation
Biological Processes
Breast cancer
Descripción
Sumario:Pathway analysis is an important step in the interpretation of single cell transcriptomic data, as it provides powerful information to detect which cellular processes are active in each individual cell. We have recently developed a protein-protein interaction network-based framework to quantify pluripotency associated pathways from scRNA-seq data. On this occasion, we extend this approach to quantify the activity of a pathway associated with any biological process, or even any list of genes. A systems-level characterization of pathway activities across multiple cell types provides a broadly applicable tool for the analysis of pathways in both healthy and disease conditions. Dysregulated cellular functions are a hallmark of a wide spectrum of human disorders, including cancer and autoimmune diseases. Here, we illustrate our method by analyzing various biological processes in healthy and cancer breast samples. Using this approach we found that tumor breast cells, even when they form a single group in the UMAP space, keep diverse biological programs active in a differentiated manner within the cluster.