Nebulosa recovers single cell gene expression signals by kernel density estimation

By José Alquicira-Hernández, Joseph E. Powell. bioRxiv, 2020

312 citations recorded by the source corpus.

Summary Data sparsity in single-cell experiments prevents an accurate assessment of gene expression when visualised in a low-dimensional space. Here, we introduce Nebulosa, an R package that uses weighted kernel density estimation to recover signals lost through drop-out or low expression. Availability and implementation Nebulosa can be easily installed from www.github.com/powellgenomicslab/Nebulosa

Subfields: Biophysics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/4118f9cf41d18a34cb1e1181db3ded50802e0103

Citations in the corpus

• Integrated analysis of multimodal single-cell data (2020, unknown): “Visualization in 6B from [51]).”