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Single-Cell Signature Explorer for comprehensive visualization of single cell signatures across scRNA-seq datasets.

Frédéric Pont | Marie Tosolini | Jean J Fournié
Nucleic acids research | 2019

The momentum of scRNA-seq datasets prompts for simple and powerful tools exploring their meaningful signatures. Here we present Single-Cell_Signature_Explorer (https://sites.google.com/site/fredsoftwares/products/single-cell-signature-explorer), the first method for qualitative and high-throughput scoring of any gene set-based signature at the single cell level and its visualization using t-SNE or UMAP. By scanning datasets for single or combined signatures, it rapidly maps any multi-gene feature, exemplified here with signatures of cell lineages, biological hallmarks and metabolic pathways in large scRNAseq datasets of human PBMC, melanoma, lung cancer and adult testis.

Pubmed ID: 31294801

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Publication data is provided by the National Library of Medicine ® and PubMed ®. Data is retrieved from PubMed ® on a weekly schedule. For terms and conditions see the National Library of Medicine Terms and Conditions.

This is a list of tools and resources that we have found mentioned in this publication.


Shiny (tool)

RRID:SCR_001626

Open source R package that provides web framework for building web applications using R. Used to create interactive web apps in native R, without needing to use HTML, CSS, or JavaScript.

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Seurat (tool)

RRID:SCR_016341

Software as R package designed for QC, analysis, and exploration of single cell RNA-seq data. Enable users to identify and interpret sources of heterogeneity from single cell transcriptomic measurements, and to integrate diverse types of single cell data.

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golang (tool)

RRID:SCR_017096

Software tool as open source programming language to build simple, reliable, and efficient software. Developed by team at Google and many contributors from open source community.

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