scRNA-Explorer: An End-user Online Tool for Single Cell RNA-seq Data Analysis Featuring Gene Correlation and Data...

Area of Science:

• Genomics
• Bioinformatics
• Computational Biology

Background:

• Single-cell RNA sequencing (scRNA-seq) generates high-dimensional data requiring complex analysis.
• Current methods often involve dimensionality reduction and feature selection to manage data complexity and identify key genes.
• Identifying genes that characterize specific cells or conditions is crucial for biological interpretation.

Purpose of the Study:

• To present scRNA-Explorer, an open-source online tool for simplified and rapid scRNA-seq data analysis.
• To enable users to interactively explore scRNA-seq datasets and investigate gene functions through expression correlations.
• To facilitate the identification of biologically relevant gene sets and their functional implications.

Main Methods:

• Interactive filtering of uninformative cells via a web interface.
• Gene correlation analysis with an added step for evaluating biological significance.
• Gene enrichment analysis of correlated genes to infer functional roles.

Main Results:

• scRNA-Explorer provides an intuitive platform for interactive scRNA-seq data exploration.
• The tool effectively identifies gene expression correlations and assesses their biological relevance.
• Gene enrichment analysis aids in discovering the functional implications of correlated genes.

Conclusions:

• scRNA-Explorer offers a user-friendly solution for rapid and simplified scRNA-seq analysis.
• The tool empowers researchers to explore gene functions and biological insights from scRNA-seq data.
• Interactive analysis of gene correlations and enrichment facilitates hypothesis generation in single-cell studies.