ArticleNature biotechnology2013
viSNE enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia.
Article in Nature biotechnology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06626555 (Pilot, Randomized, Open-Label, Non-Active Comparator Controlled Clinical Trial to Evaluate the Effects of Letermovir Prophylaxis on T-cell Immune Activation in Participants With Treated HIV-1 Infection), which is not on this map. Cited by 905 papers.
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Pilot, Randomized, Open-Label, Non-Active Comparator Controlled Clinical Trial to Evaluate the Effects of Letermovir Prophylaxis on T-cell Immune Activation in Participants With Treated HIV-1 Infection
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905 citing papers in PubMed.
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845 more citing papers are in PubMed but not listed here.
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Abstract
New high-dimensional, single-cell technologies offer unprecedented resolution in the analysis of heterogeneous tissues. However, because these technologies can measure dozens of parameters simultaneously in individual cells, data interpretation can be challenging. Here we present viSNE, a tool that allows one to map high-dimensional cytometry data onto two dimensions, yet conserve the high-dimensional structure of the data. viSNE plots individual cells in a visual similar to a scatter plot, while using all pairwise distances in high dimension to determine each cell's location in the plot. We integrated mass cytometry with viSNE to map healthy and cancerous bone marrow samples. Healthy bone marrow automatically maps into a consistent shape, whereas leukemia samples map into malformed shapes that are distinct from healthy bone marrow and from each other. We also use viSNE and mass cytometry to compare leukemia diagnosis and relapse samples, and to identify a rare leukemia population reminiscent of minimal residual disease. viSNE can be applied to any multi-dimensional single-cell technology.
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