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Single-cell expression measurements are commonly affected by high levels of technical noise, posing challenges for data analysis and interpretation. Here, we propose ENHANCE, an algorithm that denoises single-cell RNA-Seq data by first performing nearest-neighbor aggregation and then inferring expression levels from principal components. We benchmark ENHANCE and three previously described methods on simulated data that closely mimic real datasets, and show that ENHANCE provides the best overall denoising accuracy.doi:10.1101/655365 fatcat:hkgg62uiyffcrdafpumzphahia