SC1

SC1 performs analysis and integration of single-cell RNA sequencing (scRNA-Seq) data and T-cell receptor (TCR) sequencing to identify cell populations, differential expression, gene enrichment, and cell cycle states.

Key Features:

• Integrated Workflow: Provides a streamlined workflow tailored for scRNA-Seq analysis.
• Informative Gene Selection: Selects informative genes using term-frequency inverse-document-frequency (TF-IDF) scores.
• Clustering and Differential Expression Analysis: Implements clustering methods and differential expression analysis to identify distinct cell populations and gene expression differences.
• Gene Enrichment and Visualization: Performs gene enrichment analysis and generates visualizations of results.
• Cell Cycle Analysis: Includes analysis of cell cycle phases and related gene expression patterns.
• TCR Sequencing Integration: Integrates T-cell receptor (TCR) sequencing data with scRNA-Seq analyses.
• Support for Multiple Sequencing Technologies: Supports multiple single-cell sequencing technologies for broad applicability.

Scientific Applications:

• Cell Population Identification: Identifies distinct cell populations and subtypes from scRNA-Seq datasets.
• Differential Expression Studies: Detects gene expression differences between cell populations or experimental conditions.
• Tissue Development Analysis: Characterizes cell-type composition and expression patterns relevant to tissue development.
• Tumor Biology and Progression: Profiles cellular heterogeneity and gene expression to study tumor biology and progression.
• Immune Repertoire and Clonotype Analysis: Analyzes TCR sequencing alongside scRNA-Seq to investigate immune repertoires and clonotypes.

Methodology:

Gene selection using term-frequency inverse-document-frequency (TF-IDF); clustering; differential expression analysis; gene enrichment analysis; cell cycle analysis; integration of T-cell receptor (TCR) sequencing; support for multiple single-cell sequencing technologies.