<i>Nebulosa</i> recovers single-cell gene expression signals by kernel density estimation
José Alquicira-Hernández, Joseph E. Powell
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.
Topics & Concepts
Kernel density estimationKernel (algebra)R packageComputer scienceComputational biologyExpression (computer science)BiologyPattern recognition (psychology)Artificial intelligenceMathematicsStatisticsEstimatorProgramming languageCombinatoricsComputational scienceSingle-cell and spatial transcriptomicsGene Regulatory Network AnalysisCell Image Analysis Techniques