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High throughput experimental approaches are increasingly allowing for the quantitative description of cellular and organismal phenotypes. Distilling these large volumes of complex data into meaningful measures that can drive biological insight remains a central challenge. In the quantitative study of development, for instance, one can resolve phenotypic measures for single cells onto their lineage history, enabling joint consideration of heritable signals and cell fate decisions. Most attempts to analyze this type of data, however, discard much of the information content contained within lineage trees. In this work we introduce a generalized metric, which we term the branch edit distance, that allows us to compare any two embryos based on phenotypic measurements in individual cells. This approach aligns those phenotypic measurements to the underlying lineage tree, providing a flexible and intuitive framework for quantitative comparisons between, for instance, Wild-Type (WT) and mutant developmental programs. We apply this novel metric to data on cell-cycle timing from over 1300 WT and RNAi-treated Caenorhabditis elegans embryos. Our new metric revealed surprising heterogeneity within this data set, including subtle batch effects in WT embryos and dramatic variability in RNAi-induced developmental phenotypes, all of which had been missed in previous analyses. Further investigation of these results suggests a novel, quantitative link between pathways that govern cell fate decisions and pathways that pattern cell cycle timing in the early embryo. Our work demonstrates that the branch edit distance we propose, and similar metrics like it, have the potential to revolutionize our quantitative understanding of organismal phenotype. Author summary: Lineage tracing has seen a renaissance as imaging and molecular technologies have made it possible to perform increasingly rich quantitative experiments in developing systems. Although the joint capture of cellular phenotypes and lineage history enables us to study how important developmental events are regulated, the volume and complexity of the data produced make it difficult to systematically discover new patterns and relationships from this data. We have developed a new way of measuring how cellular phenotypes, such as the length of the cell cycle, differ between cell lineages and applied this approach to the characterization of embryonic development in Caenorhabditis elegans, a microscopic roundworm that has long been used as a model system for studying the regulation of cellular differentiation during embryonic development. Our quantitative and unbiased approach allowed us to describe previously unknown patterns of cell cycle timing between the major lineages of the C. elegans embryo, discover surprising differences between populations of wild type embryos and between embryos in which a panel of genes essential for embryonic development had been perturbed, and provided a quantitative link between cell fate and cell cycle timing patterns that have been widely observed in development but not well understood. These findings highlight the power of our approach and motivate continued investigation of the links between cell cycle timing and cell fate in developing embryos and stem cells. [ABSTRACT FROM AUTHOR]