IRIS-FGM

IRIS-FGM analyzes single-cell RNA sequencing (scRNA-Seq) data to identify and interpret functional gene modules (FGMs) and to derive co-expression/co-regulation patterns, cell-type clusters, differential expression, and functional enrichment.

Key Features:

• Functional Gene Module Analysis: Identifies functional gene modules (FGMs) from scRNA-Seq data using QUBIC2.
• Integration with Analysis Pipelines: Implemented in R (version 3.6) and accepts Seurat objects as input for integration with Seurat-based workflows.
• Co-expression and Co-regulation Detection: Detects co-expressed and co-regulated FGMs to reveal gene interaction structures.
• Cell Type Prediction and Clustering: Predicts cell types and performs cell clustering to characterize cellular heterogeneity.
• Differential Expression Analysis: Identifies differentially expressed genes across clusters or cell types.
• Functional Enrichment Analysis: Performs functional enrichment to interpret the biological significance of FGMs and gene sets.

Scientific Applications:

• Cancer Research: Dissects tumor cellular heterogeneity and gene-module–level programs relevant to cancer biology.
• Complex Disease Studies: Characterizes cell-type–specific gene modules and regulatory patterns in complex diseases.
• Signature Gene and Biomarker Discovery: Supports discovery of signature genes and differentially expressed candidates for downstream validation.

Methodology:

IRIS-FGM uses QUBIC2 for FGM identification, operates in R (version 3.6) with Seurat objects as input, and implements analyses for co-expression/co-regulation detection, cell clustering and type prediction, differential expression, and functional enrichment.