The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Automated mapping of phenotype space with single-cell data
Open accessAbstract
Accurate identification of cell subsets in complex populations is key to discovering novelty in multidimensional single-cell experiments. We present X-shift (http://web.stanford.edu/~samusik/vortex/), an algorithm that processes data sets using fast k-nearest-neighbor estimation of cell event density and arranges populations by marker-based classification. X-shift enables automated cell-subset clustering and access to biological insights that 'prior knowledge' might prevent the researcher from discovering.
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Cites
Bendall, S. C., Simonds, E. F., Qiu, P., Amir, E.-A. D., Krutzik, P. O., Finck, R., Bruggner, R. V., Melamed, R., Trejo, A., Ornatsky, O. I., et al. (2011) · Science · doi:10.1126/science.1198704 · Cited by 2,279
Self-citationExtracting a cellular hierarchy from high-dimensional cytometry data with SPADE
Qiu, P., Simonds, E. F., Bendall, S. C., Gibbs, K. D., Bruggner, R. V., Linderman, M. D., Sachs, K., Nolan, G. P., & Plevritis, S. K. (2011) · Nature Biotechnology · doi:10.1038/nbt.1991 · Cited by 956
Self-citationBendall, S. C., Davis, K. L., Amir, E.-A. D., Tadmor, M. D., Simonds, E. F., Chen, T. J., Shenfeld, D. K., Nolan, G. P., & Pe’er, D. (2014) · Cell · doi:10.1016/j.cell.2014.04.005 · Cited by 906
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Cited by
Dimensionality reduction for visualizing single-cell data using UMAP
Becht, E., McInnes, L., Healy, J., Dutertre, C.-A., Kwok, I. W. H., Ng, L. G., Ginhoux, F., & Newell, E. W. (2019) · Nature Biotechnology · doi:10.1038/nbt.4314 · Cited by 5,358
Deep profiling of mouse splenic architecture with CODEX multiplexed imaging
Goltsev, Y., Samusik, N., Kennedy-Darling, J., Bhate, S., Hale, M., Vazquez, G., Black, S., & Nolan, G. P. (2018) · Cell · doi:10.1016/j.cell.2018.07.010 · Cited by 1,501
“Moreover, application of X-shift phenotype-mapping algorithm (Samusik et al., 2016) tailored to parsing the multidimensional single-cell data enabled the detection of rare cells types (such as CD4 MHCII [Lti] cells, CD11c B cells [ABC cells]) and simultaneous placement of those cells in the tissue architecture.”
NBB-Psy, Böttcher, C., Schlickeiser, S., Sneeboer, M. A. M., Kunkel, D., Knop, A., Paza, E., Fidzinski, P., Kraus, L., Snijders, G. J. L., et al. (2019) · Nature Neuroscience · doi:10.1038/s41593-018-0290-2 · Cited by 436
An ex vivo tumor fragment platform to dissect response to PD-1 blockade in cancer
Voabil, P., de Bruijn, M., Roelofsen, L. M., Hendriks, S. H., Brokamp, S., van den Braber, M., Broeks, A., Sanders, J., Herzig, P., Zippelius, A., et al. (2021) · Nature Medicine · doi:10.1038/s41591-021-01398-3 · Cited by 380
Fundamental limits on dynamic inference from single-cell snapshots
Weinreb, C., Wolock, S., Tusi, B. K., Socolovsky, M., & Klein, A. M. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1714723115 · Cited by 341
Metadata
- Authors
- Samusik, N., Good, Z., Spitzer, M. H., Davis, K. L., & Nolan, G. P.
- Venue
- Nature Methods
- Published
- 2016-05-16
- Volume
- 13
- Issue
- 6
- Pages
- 493-496
- ISSN
- 1548-7091 (ISSN-L)
- 1548-7105
- OpenAlex
- W2358421111
- Cited by
- 419
- References
- 3
- FWCI
- 13.69
- Type
- journal article
- Language
- en
- Open access
- green
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- Samusik, N., Good, Z., Spitzer, M. H., Davis, K. L., & Nolan, G. P. (2016). Automated mapping of phenotype space with single-cell data. Nature Methods. https://doi.org/10.1038/nmeth.3863
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
