Sincell: an R/Bioconductor package for statistical assessment of cell-state hierarchies from single-cell RNA-seq: Fig. 1.

Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells

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Decoding the regulatory network of early blood development from single-cell gene expression measurements

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Single-Cell Trajectory Detection Uncovers Progression and Regulatory Coordination in Human B Cell Development

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The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells

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Massively Parallel Single-Cell RNA-Seq for Marker-Free Decomposition of Tissues into Cell Types

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viSNE enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia

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Quantitative assessment of single-cell RNA-sequencing methods

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Extracting a cellular hierarchy from high-dimensional cytometry data with SPADE

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