Automated mapping of phenotype space with single-cell data

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


Accurate identification of cell subsets in complex populations is key to discovering novelty in multidimensional single-cell experiments. We present X-shift (, 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.

Publication types

  • Research Support, U.S. Gov't, P.H.S.
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Algorithms
  • Animals
  • Bone Marrow Cells / cytology
  • Cluster Analysis
  • Image Enhancement
  • Image Interpretation, Computer-Assisted / methods*
  • Male
  • Mice, Inbred C57BL
  • Pattern Recognition, Automated / methods*
  • Sensitivity and Specificity
  • Single-Cell Analysis / methods*