scStudio

scStudio performs modular analysis of single-cell RNA sequencing (scRNA-seq) data to characterize cellular heterogeneity, identify differentially expressed genes, and interpret associated biological pathways.

Key Features:

• Data retrieval from GEO: Automatic retrieval of datasets from the Gene Expression Omnibus (GEO) for access to public scRNA-seq data.
• Custom data upload and file format support: Support for uploading custom datasets in various file formats.
• Dataset integration: Integration of multiple datasets to enable comparative and combined analyses.
• Modular analysis pipeline: Performs quality control, normalization, dimensionality reduction, clustering, differential expression analysis, and functional enrichment analysis for scRNA-seq data.
• Flexibility and parameter optimization: Provides a range of analysis methods with options for parameter optimization.

Scientific Applications:

• Cellular heterogeneity analysis: Characterizing cell populations and heterogeneity using clustering and single-cell expression profiles.
• Differential expression and pathway analysis: Identifying differentially expressed genes and performing functional enrichment to link gene sets to biological pathways.
• Comparative and domain-specific studies: Comparative analyses across conditions and applications in developmental biology, oncology, and immunology.

Methodology:

Automatic retrieval from GEO, import of custom datasets in various file formats, dataset integration, quality control, normalization, dimensionality reduction, clustering, differential expression analysis, and functional enrichment analysis with options for parameter optimization.