Format

Send to

Choose Destination
Nat Methods. 2016 Jun;13(6):493-6. doi: 10.1038/nmeth.3863. Epub 2016 May 16.

Automated mapping of phenotype space with single-cell data.

Author information

1
Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, California, USA.
2
Department of Pathology, Stanford University School of Medicine, Stanford, California, USA.
3
Department of Pediatric Hematology and Oncology, Stanford University School of Medicine, Stanford, California, USA.

Abstract

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.

PMID:
27183440
PMCID:
PMC4896314
DOI:
10.1038/nmeth.3863
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for Nature Publishing Group Icon for PubMed Central
Loading ...
Support Center