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 principales: Senra, Daniela, Guisoni, Nara Cristina, Diambra, Luis Aníbal
Formato: Articulo
Lenguaje:Inglés
Publicado: 2023
Materias:
Biología
scRNA-seq
Protein-protein interaction networks
Cell annotation
Biological Processes
Breast cancer
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/160415
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-160415
record_format dspace
spelling I19-R120-10915-1604152023-11-22T20:06:41Z http://sedici.unlp.edu.ar/handle/10915/160415 Cell annotation using scRNA-seq data: a protein-protein interaction network approach Senra, Daniela Guisoni, Nara Cristina Diambra, Luis Aníbal 2023 2023-11-22T16:45:13Z en Biología scRNA-seq Protein-protein interaction networks Cell annotation Biological Processes Breast cancer 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. Centro Regional de Estudios Genómicos Articulo Articulo http://creativecommons.org/licenses/by-nc-nd/4.0/ Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) application/pdf
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Biología
scRNA-seq
Protein-protein interaction networks
Cell annotation
Biological Processes
Breast cancer
spellingShingle Biología
scRNA-seq
Protein-protein interaction networks
Cell annotation
Biological Processes
Breast cancer
Senra, Daniela
Guisoni, Nara Cristina
Diambra, Luis Aníbal
Cell annotation using scRNA-seq data: a protein-protein interaction network approach
topic_facet Biología
scRNA-seq
Protein-protein interaction networks
Cell annotation
Biological Processes
Breast cancer
description 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.
format Articulo
Articulo
author Senra, Daniela
Guisoni, Nara Cristina
Diambra, Luis Aníbal
author_facet Senra, Daniela
Guisoni, Nara Cristina
Diambra, Luis Aníbal
author_sort Senra, Daniela
title Cell annotation using scRNA-seq data: a protein-protein interaction network approach
title_short Cell annotation using scRNA-seq data: a protein-protein interaction network approach
title_full Cell annotation using scRNA-seq data: a protein-protein interaction network approach
title_fullStr Cell annotation using scRNA-seq data: a protein-protein interaction network approach
title_full_unstemmed Cell annotation using scRNA-seq data: a protein-protein interaction network approach
title_sort cell annotation using scrna-seq data: a protein-protein interaction network approach
publishDate 2023
url http://sedici.unlp.edu.ar/handle/10915/160415
work_keys_str_mv AT senradaniela cellannotationusingscrnaseqdataaproteinproteininteractionnetworkapproach
AT guisoninaracristina cellannotationusingscrnaseqdataaproteinproteininteractionnetworkapproach
AT diambraluisanibal cellannotationusingscrnaseqdataaproteinproteininteractionnetworkapproach
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