HUSCH: an integrated single-cell transcriptome atlas for human tissue gene expression visualization and analyses.

Area of Science:

• Genomics
• Bioinformatics
• Cell Biology

Background:

• Single-cell RNA sequencing (scRNA-seq) advances cell type heterogeneity characterization.
• Publicly available scRNA-seq datasets present integration and reuse challenges.
• Understanding human cell type gene expression is vital for differentiation and disease research.

Purpose of the Study:

• To develop an atlas-scale curated database for human single-cell transcriptomic data.
• To facilitate data integration, analysis, and reuse of diverse scRNA-seq datasets.
• To provide a comprehensive resource for exploring human tissue gene expression patterns.

Main Methods:

• Integrated 185 high-quality human scRNA-seq datasets comprising nearly 3 million cells.
• Uniformly processed and annotated all data using a standardized workflow.
• Developed modules for single dataset and single tissue analyses, including data integration and batch correction.

Main Results:

• Created the Human Universal Single Cell Hub (HUSCH) database (http://husch.comp-genomics.org).
• HUSCH provides interactive visualization, differential gene expression, functional, transcription regulator, and cell-cell interaction analyses.
• Enabled harmonized analysis of gene expression across multiple tissues and datasets.

Conclusions:

• HUSCH serves as a flexible and comprehensive portal for human single-cell gene expression data.
• The database supports searching, visualizing, analyzing, and downloading single-cell data.
• Facilitates deeper understanding of human cell type-specific gene expression and its implications in health and disease.