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Motivation: Single-cell gene expression profiling technologies can map the cell states in a tissue or organism. As these technologies become more common, there is a need for computational tools to explore the data they produce. In particular, existing data visualization approaches are imperfect for studying continuous gene expression topologies. Results: Force-directed layouts of k-nearest-neighbor graphs can visualize continuous gene expression topologies in a manner that preservesdoi:10.1093/bioinformatics/btx792 pmid:29228172 pmcid:PMC6030950 fatcat:xslrq5jxijctzoyucbmsztq4me