scCB2

scCB2 distinguishes real cells from empty droplets in droplet-based single cell RNA-seq experiments, especially for 10x Chromium, by implementing a cluster-level statistical testing approach that outperforms single-barcode-level methods for low count barcodes and homogeneous sequencing libraries while controlling FDR.

Key Features:

• Cluster-level testing: Clusters similar barcodes and calculates Monte-Carlo p-value for each cluster to test against background distribution.
• Low count barcode handling: Outperforms single-barcode-level tests in dealing with low count barcodes.
• Homogeneous sequencing library compatibility: Maintains performance on homogeneous sequencing libraries while keeping FDR well controlled.
• 10x Chromium optimization: Specifically optimized for droplet-based single cell RNA-seq experiments, particularly 10x Chromium data.

Scientific Applications:

• Cell detection in droplet-based scRNA-seq: Identifies real cells versus empty droplets in droplet-based single cell RNA-seq experiments.
• Quality control in single-cell studies: Provides statistically rigorous cell filtering with controlled FDR for downstream single-cell analyses.

Methodology:

scCB2 clusters similar barcodes and calculates Monte-Carlo p-value for each cluster to test against background distribution.