New approaches to lineage tracking have allowed the study of differentiation in multicellular organisms over many generations of cells. Understanding the phenotypic variability observed in these lineage trees requires new statistical methods. Whereas an invariant cell lineage, such as that for the nematode Caenorhabditis elegans, can be described by a lineage map, defined as the pattern of phenotypes overlaid onto the binary tree, a traditional lineage map is static and does not describe the variability inherent in the cell lineages of higher organisms. Here, we introduce lineage variability maps which describe the pattern of second-order variation in lineage trees. These maps can be undirected graphs of the partial correlations between every lineal position, or directed graphs showing the dynamics of bifurcated patterns in each subtree. We show how to infer these graphical models for lineages of any depth from sample sizes of only a few pedigrees. This required developing the generalized spectral analysis for a binary tree, the natural framework for describing tree-structured variation. When tested on pedigrees from C. elegans expressing a marker for pharyngeal differentiation potential, the variability maps recover essential features of the known lineage map. When applied to highly-variable pedigrees monitoring cell size in T lymphocytes, the maps show that most of the phenotype is set by the founder naive T cell. Lineage variability maps thus elevate the concept of the lineage map to the population level, addressing questions about the potency and dynamics of cell lineages and providing a way to quantify the progressive restriction of cell fate with increasing depth in the tree.

Abstract Summary: We describe a modular MATLAB® Toolbox named TACTICS for time-lapse image analysis that meets several requirements not generally offered by currently available software packages: (i) the ability to assess quality of extracted imaging information by directly linking data end points to the original position, (ii) massively parallel analysis of each parameter, for flow cytometry-like assessment of possible relationships between parameters within sub-populations of the images, (iii) options for user control of the tracking such as an interface to restrict the analysis region, (iv) manual correction of automated processes and (v) user interfaces for post-tracking analysis that is linked to the original images, including options to view cell pedigrees and normalized polarization ratios based on fluorescence ratiometric measurements. Availability and implementation: We provide TACTICS source code as well as video tutorials, data sample and comprehensive user guide on the TACTICS toolbox website (http://www.tactics-toolbox.com). Installation of TACTICS requires MATLAB 7.6 (R2008a) with the presence of Image Processing Toolbox™ and Statistics Toolbox™. Contact: [email protected].