webMCP-counter

webMCP-counter quantifies immune and stromal cell populations from bulk transcriptomic data in human and murine samples to estimate tissue cellular composition.

Key Features:

• Underlying algorithms: Implements the MCP-counter and mMCP-counter gene-signature-based algorithms derived from their R packages.
• Gene expression signatures: Uses predefined gene expression signatures to estimate the abundance of specific immune and stromal cell types.
• Supported organisms: Supports analysis of human and murine samples.
• Input data: Operates on bulk transcriptomic data, including bulk RNA-seq.

Scientific Applications:

• Oncology: Quantifies immune and stromal composition of tumor microenvironments for cancer studies.
• Immunology: Profiles immune cell populations within heterogeneous tissue samples for immunological research.
• Disease mechanisms and therapeutic response: Provides cellular composition estimates from bulk RNA-seq to support investigations of disease mechanisms and therapeutic responses.

Methodology:

Estimates cell-type abundance from bulk transcriptomic data using predefined gene expression signatures and algorithms from the MCP-counter and mMCP-counter R packages, providing composition estimates without single-cell resolution.