Single-Cell Virtual Cytometer allows user-friendly and versatile analysis and visualization of multimodal single cell...

Area of Science:

• Single-cell multi-omics analysis
• Computational biology
• Immunogenomics

Background:

• Single-cell technologies generate large multimodal datasets (e.g., transcriptomes, immunophenotypes).
• Existing methods for pre-processing and integrating multimodal single-cell data are numerous.
• A gap exists in user-friendly software for simultaneous visualization of immunophenotype and transcriptome data.

Purpose of the Study:

• Introduce Single-Cell Virtual Cytometer, an open-source software.
• Provide flow cytometry-like visualization for pre-processed multi-omics single-cell data.
• Facilitate integrated analysis of transcriptomes and epitopes.

Main Methods:

• Development of an open-source software tool named Single-Cell Virtual Cytometer.
• Utilized CITE-seq data from peripheral blood mononuclear cells (PBMCs) of a healthy donor.
• Demonstrated integrated analysis of transcriptomes and epitopes for T lymphocyte maturation.

Main Results:

• Single-Cell Virtual Cytometer enables simultaneous visualization of immunophenotype and transcriptome data.
• The software facilitates exploration of multi-omics single-cell datasets.
• Illustrates integrated analysis of transcriptomes and epitopes in human peripheral T lymphocytes.

Conclusions:

• Single-Cell Virtual Cytometer is a free, open-source, and user-friendly tool.
• It serves as a unique resource for biologists analyzing multimodal single-cell data.
• Enhances the integrated analysis of transcriptomic and immunophenotypic information.