Figure 10.

Graphical quality control limits. The full population of triplicate sets shown in Figure 9 is here represented as a histogram of the individual standard deviations for velocities from triplicate wells of KM101 cells (black bars) and MG-63 cells (white bars). Presented in this fashion, the data are useful for graphically estimating quality control limits and identifying outliers. Data from images of MG-63 cells are shown to be "well behaved" in comparison to KM101 cells, which exhibit a number of outliers to the right of the "normal" limit expected for the tail. Arrows indicate positions of "3 sigma" limits that are based on the observed percentage (99.7%) of observations (rather than on a more complex transformation of the data according to a mathematical model). In the case of MG-63 cells, the limit (block arrow) excludes several adjacent triplicate sets that are properly part of the distribution. Two certified MG-63 outliers are not readily visible on this chart at 0.40–0.41 um/min. In the case of KM101 cells, the "3-sigma" limit (solid arrow) more haphazardly cuts off a chain of outliers. As described in the text, one source of KM101 outliers was identified by manual viewing of tracked objects in the image sequences, and may lead to a rational filtering method that would improve the data on both sides of the control limit for KM101 cells. Since the average variance for triplicate velocity measurements correlated to some extent with average velocity (see Figure 9), a more refined approach to quality control would involve first ranking the data according to average velocity. Presumably the next step would be to determine whether a single member of the outlying triplicate sets should be discarded in favour of preserving the remaining two measurements in each case.

Bahnson et al. BMC Cell Biology 2005 6:19   doi:10.1186/1471-2121-6-19
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