Nebulosa recovers single-cell gene expression signals by kernel density estimation

Abstract

Abstract Summary Data sparsity in single-cell experiments prevents an accurate assessment of gene expression when visualized 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. Supplementary information Supplementary data are available at Bioinformatics online.