Determining Physical Mechanisms of Gene Expression Regulation from Single Cell Gene Expression Data
Fig 4
Application of SABEC to hematopoietic stem cells and progenitor populations.
SABEC was used to identify subpopulations of cells in the Moignard et al. dataset and to identify specific cells that do not cluster well with the other cells of the same type. (A) Hierarchical clustering was applied to the SABEC consensus matrix to reveal six subpopulations of HSC in subfigure. (Bi) The expected hematopoiesis differentiation tree is shown–the names of the cell populations are color-coded to match the vertical and horizontal bars in A. (Bii) We hypothesized a possible alternative differentiation tree, based on the clustering results. (C) Another application of this clustering method is to remove possible outliers, which may have arisen due to poorly sorted cells or extrinsic variability. Within each cell population (i.e. CLP (i), GMP (ii), HSC (iii), LMPP (iv) and PreM (v)), we sorted the cells by how often the cells are clustered with other cells from the same FACS label (% match). The vertical lines depict thresholds selected to approximately correspond to the region with the steepest slope– cells to the left are disregarded as outliers in the EPiK analysis.