TABLE 1:

Comparison of DI measurements from classical two-state analysis, STADIA two-state analysis (i.e., STADIA with k = 1), and STADIA analysis with full classification. Top row of each subtable: classical two-state analysis method (Materials and Methods Section 5.3) performed by identifying only major peaks and valleys (Figure 2 A–B). Second row of each subtable: STADIA analysis with classification limited to two states: only growth and shortening. Third row of each subtable: STADIA analysis with classification limited to growth, shortening, and flat stutters. Bottom row of each subtable: STADIA analysis using full results of the classification stage (Figure 4; Results Section 2.3). All STADIA analyses used the fine-grained length-history approximation generated by the segmentation stage of STADIA (Figure 2D) but differed in the settings for the classification stage. These data show that there is general, but not exact, agreement between the analysis methods as applied to each dataset. V_growth and V_short measurements are listed as mean ± standard deviation over the set of all segments identified in each type of behavior. See Supplemental Figure S1.9 for the number of segments in each cluster from the STADIA full analysis. See Materials and Methods Sections 5.1.4 and 5.2.2 for the number of MTs and total observation times in each dataset. 
†,‡: Because depolymerizations in the in vitro datasets were not captured in their entirety (see examples in Figure 1D), rescue frequencies are not reported (†), and negative slope segments were separated into only two clusters, yielding only two V_short measurements in the full STADIA analysis (‡), instead of three as seen with the in silico data.