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alona: a web server for single-cell RNA-seq analysis.

Oscar Franzén1, Johan L M Björkegren1,2

  • 1Department of Medicine, Integrated Cardio Metabolic Centre, Karolinska Institutet, Huddinge 14157, Sweden.

Bioinformatics (Oxford, England)
|April 24, 2020
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Summary

A new web server, alona, offers user-friendly analysis for single-cell RNA sequencing (scRNA-seq) data. It integrates popular algorithms for quality control, clustering, and cell type annotation, simplifying complex single-cell data exploration.

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Area of Science:

  • Genomics and Bioinformatics
  • Computational Biology
  • Molecular Biology

Background:

  • Single-cell RNA sequencing (scRNA-seq) is a powerful technology for analyzing gene expression at the individual cell level.
  • The increasing volume and complexity of scRNA-seq data necessitate robust and accessible analysis tools.
  • Existing software solutions may lack flexibility or user-friendliness for diverse research needs.

Purpose of the Study:

  • To develop a user-friendly web server, alona, for comprehensive single-cell RNA sequencing data analysis.
  • To integrate multiple popular single-cell analysis algorithms into a flexible and accessible pipeline.
  • To facilitate the discovery of new cell types and the creation of cell type atlases.

Main Methods:

  • Development of a web server (alona) incorporating popular single-cell analysis algorithms.
  • Implementation of a flexible pipeline for quality filtering, normalization, batch correction, and clustering.
  • Integration of graph-based clustering and JavaScript-based visualization for interactive data exploration and cell type annotation using marker genes.

Main Results:

  • alona provides a comprehensive suite of tools for scRNA-seq data analysis, including quality control, normalization, batch correction, and differential gene expression analysis.
  • The web server enables interactive visualization of cell clusters and gene expression patterns directly in the web browser.
  • Cell type identification is supported through comprehensive marker gene collections or custom user-defined markers.

Conclusions:

  • alona offers a flexible, user-friendly, and integrated platform for analyzing single-cell RNA sequencing data.
  • The tool democratizes access to advanced scRNA-seq analysis, supporting cell type discovery and atlasing efforts.
  • The web server and associated Python package are available for broad scientific adoption.