MultiK

MultiK determines the optimal number of clusters in single-cell RNA sequencing (scRNA-seq) data to enable objective identification and characterization of distinct cell populations.

Key Features:

• Objective estimation of K: MultiK provides an objective framework to estimate the optimal cluster number (K) for scRNA-seq clustering.
• Multi-resolution assessment: It assesses clustering at multiple resolutions to capture both broad and fine-scale population structures.
• Consensus clustering aggregation: It integrates consensus clustering by aggregating results from multiple clustering runs to improve robustness and reproducibility of identified clusters.

Scientific Applications:

• Cell-type and population discovery: Applied to scRNA-seq studies to improve identification of cell-type populations and interpretation of cellular heterogeneity.

Methodology:

MultiK uses a consensus clustering framework that aggregates multiple clustering runs across different resolutions to select reproducible optimal K values.