QClus

QClus clusters and filters droplets in single-nuclei RNA sequencing data using cell-type-specific marker gene expression to remove empty and highly contaminated droplets, improving data quality and reliability in challenging samples.

Key Features:

• Cell-type-specific marker gene clustering: QClus uses cell-type-specific marker gene expression as additional metrics to cluster nuclei and distinguish valid droplets from contaminants.
• Empty droplet filtering: QClus identifies and removes empty droplets that contribute background signal.
• High-contamination droplet filtering: QClus filters highly contaminated droplets that mask cell-type-specific signals.
• Robust retention of nuclei numbers: QClus robustly retains numbers of nuclei within the expected range across samples with varying nuclei counts and contamination levels.
• Automation with user-adjustability: QClus provides automated filtering with flexibility for diverse experimental needs and datasets.
• High processing reliability: QClus recorded no processing failures in benchmarking analysis across 252 samples and over 1.9 million nuclei.

Scientific Applications:

• Challenging human tissue snRNA-seq analysis: QClus enhances single-nuclei RNA sequencing data quality for human tissues where incomplete removal of background signal masks cell-type-specific signals.
• Large-scale dataset benchmarking: QClus was validated across six datasets consisting of 252 samples and over 1.9 million nuclei, achieving the highest quality in the greatest number of samples over all evaluated quality metrics.

Methodology:

QClus clusters nuclei using cell-type-specific marker gene expression as additional metrics, then filters empty and highly contaminated droplets. Benchmarking was performed against seven alternative methods.