Nebulosa

Nebulosa recovers and visualizes gene expression signals in single-cell RNA-seq and ATAC-seq data by applying weighted kernel density estimation that incorporates cell similarity to mitigate sparsity from drop-out and low expression.

Key Features:

• Signal Recovery: Recovers gene expression signals obscured by drop-out events or low expression levels to improve detection in single-cell data.
• Kernel Density Estimation (weighted): Uses weighted kernel density estimation that incorporates cell–cell similarity to perform a convolution of cell features and enhance expression pattern resolution.
• Visualization Enhancement: Mitigates sparsity in low-dimensional visualizations and when overlaying clustering to annotate cell types, reducing unclear or misleading representations.

Scientific Applications:

• Single-Cell RNA-seq and ATAC-seq Analysis: Addresses dataset sparsity to facilitate more accurate single-cell gene expression and chromatin accessibility analyses.
• Data Interpretation: Provides clearer insights into cellular heterogeneity and dynamics to support studies of complex biological processes and disease mechanisms.

Methodology:

Weighted kernel density estimation that convolves cell features using cell–cell similarity to smooth expression signals and recover signals lost to drop-out and low expression.