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An accessible, interactive GenePattern Notebook for analysis and exploration of single-cell transcriptomic data

Single-cell RNA sequencing (scRNA-seq) has emerged as a popular method to profile gene expression at the resolution of individual cells. While there have been methods and software specifically developed to analyze scRNA-seq data, they are most accessible to users who program. We have created a scRNA...

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Detalles Bibliográficos
Autores principales: Mah, Clarence K., Wenzel, Alexander T., Juarez, Edwin F., Tabor, Thorin, Reich, Michael M., Mesirov, Jill P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: F1000 Research Limited 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6611141/
https://www.ncbi.nlm.nih.gov/pubmed/31316748
http://dx.doi.org/10.12688/f1000research.15830.2
Descripción
Sumario:Single-cell RNA sequencing (scRNA-seq) has emerged as a popular method to profile gene expression at the resolution of individual cells. While there have been methods and software specifically developed to analyze scRNA-seq data, they are most accessible to users who program. We have created a scRNA-seq clustering analysis GenePattern Notebook that provides an interactive, easy-to-use interface for data analysis and exploration of scRNA-Seq data, without the need to write or view any code. The notebook provides a standard scRNA-seq analysis workflow for pre-processing data, identification of sub-populations of cells by clustering, and exploration of biomarkers to characterize heterogeneous cell populations and delineate cell types.