scMuffin: an R package to disentangle solid tumor heterogeneity by single-cell gene expression analysis

Area of Science:

• Bioinformatics
• Genomics
• Cancer Research

Background:

• Solid tumors exhibit complex cellular heterogeneity, hindering effective cancer treatment development.
• Bulk RNA sequencing struggles to identify specific cell subpopulations crucial for cancer progression.
• Single-cell (SC) gene expression analysis is vital for dissecting tumor cellularity.

Purpose of the Study:

• To introduce scMuffin, an R package for characterizing cell identity in solid tumors using SC gene expression data.
• To provide a comprehensive suite of analytical tools for SC data from solid tumors.
• To facilitate the identification of critical cell subpopulations and their genomic underpinnings.

Main Methods:

• scMuffin offers functions to calculate scores for marker gene expression, pathway activity, and cell state trajectories.
• The package enables analysis of Copy Number Variations (CNVs), transcriptional complexity, and proliferation states.
• It integrates diverse evidence to distinguish cell types and link genomic aberrations to phenotypes.

Main Results:

• scMuffin was validated using public SC expression datasets of human high-grade gliomas.
• Analyses revealed potential links between chromosomal amplifications and invasive tumor phenotypes.
• Findings suggest chromosomal amplifications may be associated with cells possessing tumor-initiating characteristics.

Conclusions:

• scMuffin effectively addresses key bioinformatics challenges in analyzing SC gene expression data from solid tumors.
• The tool aids in distinguishing normal and tumor cells and defining cell identities.
• scMuffin facilitates the identification of subtle differences between cell subtypes and states.