Automated mapping of phenotype space with single-cell data
Samusik, N., Good, Z., Spitzer, M.H. et al.
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.
Samusik, N., Good, Z., Spitzer, M.H. et al. "Automated mapping of phenotype space with single-cell data" Nature Methods (2016): 493–6