Nebulosa

Nebulosa recovers single-cell gene expression signals lost through drop-out or low expression using weighted kernel density estimation for enhanced visualization of single-cell data.

Key Features:

• Gene-Weighted Density Estimation: Nebulosa applies kernel density estimation weighted by gene expression to recover signals from dropped-out features in single-cell data.
• Joint Expression Inspection: Nebulosa enables the inspection of joint expression from multiple features such as genes simultaneously.
• Object Compatibility: Nebulosa supports Seurat and SingleCellExperiment objects as input formats.

Scientific Applications:

• Single-Cell Data Visualization: Nebulosa provides enhanced visualization of single-cell data in low-dimensional space by recovering signals lost to data sparsity.
• Drop-Out Signal Recovery: Nebulosa addresses data sparsity in single-cell experiments that prevents accurate assessment of gene expression in low-dimensional visualizations.

Methodology:

Nebulosa uses weighted kernel density estimation to recover signals lost through drop-out or low expression in single-cell data.