CardioShift: Resolving cell-to-cell functional heterogeneity in hiPSC-derived cardiomyocytes from high-throughput single-cell imaging

CardioShift applied to hiPSC-derived cardiomyocytes resolves that cell-to-cell variability is the largest variance source for most functional parameters, using 32,818 Ca2+ transients and 10,719 contractility-lipid profiles.

• Why it matters: Well-averaged high-content screening can hide condition-dependent phenotypes, and single-cell analyses risk pseudoreplication unless nested variance from cells-within-wells is handled correctly.
• What they did: The open-source framework maps single-cell distributions while accounting for nested variance structure, then uses unsupervised clustering on Ca2+ transients and contractility-lipid profiles.
• The result: Cell-to-cell variability is linked to most functional parameters, and clustering finds a condition-dependent lipid-accumulating cellular state with baseline contraction kinetics that well- and single-cell averaging approaches did not detect.

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