eDetect: A Fast Error Detection and Correction Tool for Live Cell Imaging Data Analysis

摘要

class="head no_bottom_margin" id="sec1title">IntroductionLive cell imaging has been widely used in monitoring cellular processes and dynamics at the single-cell level (, , ). During the course of these studies, large volumes of time-lapse images are often generated by automatic microscopes, which poses a challenge in quantifying cellular dynamics from these datasets with high precision (). In the past, computational tools have been developed to enable automated analysis of large image datasets (, , , , , , , ). However, the errors in the automated analyses impaired the accuracy in quantifying long-term single-cell dynamics. In most cases, fully automatic algorithms cannot guarantee 100% accuracy (). Even a small portion of errors can result in a much larger amount of false cell lineages (). Therefore manual inspection and correction are needed ().Several tools have provided functions to manually correct image data analysis results. For example, CellProfiler and qTfy allow the users to manually edit the contours of segmented objects one by one (href="#bib2" rid="bib2" class=" bibr popnode">Carpenter et al., 2006, href="#bib7" rid="bib7" class=" bibr popnode">Hilsenbeck et al., 2016). In addition, CellTracker, NucliTrack, LEVER, and tTt support manual track editing (href="#bib3" rid="bib3" class=" bibr popnode">Cooper et al., 2017, href="#bib7" rid="bib7" class=" bibr popnode">Hilsenbeck et al., 2016, href="#bib12" rid="bib12" class=" bibr popnode">Piccinini et al., 2016, href="#bib21" rid="bib21" class=" bibr popnode">Winter et al., 2016). These tools are useful, but an approach is still needed to improve the efficiency of data curation.Here, we report an error detection and correction tool for live cell imaging data analysis (eDetect). In eDetect, we proposed a new gating approach to classify flawed segmentation and tracking results by visualizing image features in scatterplots based on principal-component analysis (PCA). As cell objects with similar appearance often aggregate in the scatterplot, we can easily detect a group of errors from voluminous time-lapse images. Similar errors can be efficiently corrected with batch operations in eDetect. In addition, eDetect uses multiple quality control steps to achieve high accuracy in the final live cell imaging analysis results. In summary, eDetect is a comprehensive software tool that integrates cell segmentation, feature extraction, cell tracking, and efficient data curation.