SCISSORTM

SCISSORTM integrates The Cancer Genome Atlas (TCGA) bulk tumor multi-omics with high-resolution single-cell transcriptomics to infer tissue-specific cell-type composition and cell-type-specific expression profiles and to associate these profiles with clinical outcomes.

Key Features:

• Integration of Multi-Omics Data: SCISSORTM combines TCGA bulk tumor multi-omics data with high-resolution single-cell transcriptomic data to enable inference of cell type-specific expression within heterogeneous samples.
• Tissue-Specific Reference: SCISSORTM incorporates over 6031 large-scale bulk samples and more than 451,917 high-granularity single-cell transcriptomic profiles across 16 cancer types as a tissue-specific reference for cell composition inference.
• Flexible Analysis Modules: SCISSORTM provides five major analysis modules with adjustable parameters to support flexible modeling and analysis.
• Clinical Outcome Correlation: SCISSORTM characterizes associations between inferred cell types or cell-type-specific expression and clinical outcomes.

Scientific Applications:

• Tumor heterogeneity analysis: Inferring cell composition and cell-type-specific expression to analyze intratumoral heterogeneity.
• Tumor microenvironment profiling: Delineating tissue-specific cellular composition of the tumor microenvironment across 16 cancer types.
• Translational and prognostic studies: Associating cellular compositions and cell-type-specific expression with clinical outcomes to inform translational research and potential therapeutic stratification.

Methodology:

Integrates TCGA bulk tumor multi-omics with single-cell transcriptomics, infers cell type-specific expression profiles from bulk transcriptomes using the single-cell reference, leverages over 6031 bulk samples and more than 451,917 single-cell profiles across 16 cancer types, and implements five analysis modules with adjustable parameters and dynamic visualization.