{
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  "Title": "VeloViz: RNA-velocity informed 2D embeddings for visualizing\ncell state trajectories",
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  "Authors@R": "c(person(given = \"Lyla\",\nfamily = \"Atta\",\nrole = c(\"aut\", \"cre\"),\nemail = \"lylaatta@jhmi.edu\",\ncomment = c(ORCID = \"0000-0002-6113-0082\")),\nperson(given = \"Jean\",\nfamily = \"Fan\",\nrole = c(\"aut\"),\nemail = \"jeanfan@jhu.edu\",\ncomment = c(ORCID = \"0000-0002-0212-5451\")),\nperson(given = \"Arpan\",\nfamily = \"Sahoo\",\nrole = c(\"aut\"),\nemail = \"asahoo1@jhu.edu\",\ncomment = c(ORCID = \"0000-0002-0325-2073\")))",
  "Description": "VeloViz uses each cell’s current observed and predicted\nfuture transcriptional states inferred from RNA velocity\nanalysis to build a nearest neighbor graph between cells in the\npopulation. Edges are then pruned based on a cosine correlation\nthreshold and/or a distance threshold and the resulting graph\nis visualized using a force-directed graph layout algorithm.\nVeloViz can help ensure that relationships between cell states\nare reflected in the 2D embedding, allowing for more reliable\nrepresentation of underlying cellular trajectories.",
  "biocViews": "Transcriptomics, Visualization, GeneExpression, Sequencing,\nRNASeq, DimensionReduction",
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