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Figure 1 | BMC Bioinformatics

Figure 1

From: MCA: Multiresolution Correlation Analysis, a graphical tool for subpopulation identification in single-cell gene expression data

Figure 1

MCA reveals the presence of subpopulations with differential regulation. A. A three species activation motif (left), its steady state distribution (center) from an SDE simulation, and the resultant correlation network (right), showing positive correlation for species with an activating interaction. B. A three species activation/inhibition motif induces positive correlation corresponding to activation and negative correlation corresponding to inhibition. C. I. Mixture of the activation and inhibition steady state data depicted in A and B. II. Correlation analysis of the subset from the lowest 30% of the Z-distribution shows significant positive X,Y correlation. III. Correlation analysis of the subset from the highest 30% of the Z-distribution shows significant negative X,Y correlation. D. Combining all subpopulations sorted by median Z value and subpopulation size into an MCA plot reveals robust separation of positive and negative correlations for subpopulations with low or high Z values, respectively.

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