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Related Experiment Video

Updated: Dec 27, 2025

Analysis of Multidimensional Microscopy Data Using Cell-ACDC
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SCelVis: exploratory single cell data analysis on the desktop and in the cloud.

Benedikt Obermayer1,2, Manuel Holtgrewe1,2, Mikko Nieminen1,3

  • 1Core Unit Bioinformatics, Berlin Institute of Health, Berlin, Germany.

Peerj
|March 3, 2020
PubMed
Summary
This summary is machine-generated.

SCelVis offers a user-friendly, web-based visualization tool for single-cell omics data, simplifying analysis for researchers without bioinformatics expertise. This flexible app supports cloud and local deployment, enhancing data interpretation and accessibility.

Keywords:
Single cellVisualizationtSNE

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Area of Science:

  • Biomedical research
  • Life sciences
  • Computational biology

Background:

  • High-dimensional single-cell omics data present analysis and interpretation challenges.
  • FAIR data management, privacy, and security are critical for clinical and translational research.
  • Current solutions often lack flexibility, being desktop-bound or reliant on proprietary cloud technologies.

Purpose of the Study:

  • To develop an accessible, web-based visualization tool for single-cell omics data.
  • To empower users without bioinformatics expertise to analyze and interpret complex datasets.
  • To provide a flexible and user-friendly platform for single-cell data exploration.

Main Methods:

  • SCelVis is implemented in Python using Dash by Plotly.
  • Available as a standalone Python package, Conda/Bioconda package, and Docker image.
  • Utilizes open standards and interfaces for broad compatibility and integration.

Main Results:

  • SCelVis provides interactive visualizations for single-cell expression and annotation.
  • Enables users to define cell groups, perform differential gene expression analysis, and download data.
  • Tested and validated using publicly available single-cell RNA sequencing data.

Conclusions:

  • SCelVis facilitates the analysis and interpretation of single-cell omics data.
  • Offers a flexible, user-friendly, and open-source solution for researchers.
  • Supports both desktop and cloud deployment, enhancing accessibility and collaboration.